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server exposing Vectros hybrid search, structured records, and RAG/document-ask to MCP-aware desktop agents (Claude Desktop, Cursor, Code, Cline, Continue, VS Code).","maintainers":[{"name":"vectros-admin","email":"admin@vectros.ai"}],"readme":"# @vectros-ai/mcp-server\n\n[![npm](https://img.shields.io/npm/v/@vectros-ai/mcp-server)](https://www.npmjs.com/package/@vectros-ai/mcp-server)\n[![license](https://img.shields.io/npm/l/@vectros-ai/mcp-server)](https://www.apache.org/licenses/LICENSE-2.0)\n\n[![Add to Cursor](https://cursor.com/deeplink/mcp-install-dark.svg)](https://cursor.com/install-mcp?name=vectros&config=eyJjb21tYW5kIjoibnB4IiwiYXJncyI6WyIteSIsIkB2ZWN0cm9zLWFpL21jcC1zZXJ2ZXIiXSwiZW52Ijp7IlZFQ1RST1NfQVBJX0tFWSI6IiJ9fQ%3D%3D)\n[![Install in VS Code](https://img.shields.io/badge/VS_Code-Install-0098FF?logo=visualstudiocode&logoColor=white)](https://insiders.vscode.dev/redirect/mcp/install?name=vectros&config=%7B%22command%22%3A%22npx%22%2C%22args%22%3A%5B%22-y%22%2C%22%40vectros-ai%2Fmcp-server%22%5D%2C%22env%22%3A%7B%22VECTROS_API_KEY%22%3A%22%22%7D%7D)\n[![Claude Desktop Extension](https://img.shields.io/badge/Claude_Desktop-Add_Extension-D97757)](https://github.com/vectros-ai/vectros-mcp-server/releases/latest/download/vectros.mcpb)\n\n> One-click badges install the **server entry** in your client. You still supply\n> a key — run `npx -y @vectros-ai/cli bootstrap` (recommended) or paste your\n> `ssk_...`. See [Connect from your client](#connect-from-your-client) and the\n> [honest caveats](#honest-caveats).\n\nA [Model Context Protocol](https://modelcontextprotocol.io) server for\n**Vectros** — a typed, multi-tenant **record store unified with hybrid\nsearch** and citation-grounded RAG. Deterministic lookups and enumeration\n*and* semantic search over one isolated, per-customer index of records and\ndocuments — so an agent gets memory that's precise, not just fuzzy recall.\nReached agent-natively here over MCP (Claude Desktop, Cursor, Claude Code,\nCline, Continue, VS Code, hosted platforms) — and the same data is\nhuman-accessible through the Vectros app + SDKs.\n\n```\nnpx -y @vectros-ai/mcp-server\n```\n\nYour agent can search your indexed corpus, query structured records,\ningest documents, and ask questions grounded against documents — reaching\nonly your tenant's data, never the public web (there are no web tools).\n\n## Quick start — one command\n\nThe fastest way to set up is the [`@vectros-ai/cli`](https://www.npmjs.com/package/@vectros-ai/cli)\n`bootstrap` command. It mints a **least-privilege scoped key** (`ssk_*`)\nbound to a narrowed AccessProfile, optionally scaffolds a use-case data\nmodel, and safe-merges the `vectros` server into your MCP client config —\nno root key, and no hand-editing JSON:\n\n```bash\nnpx -y @vectros-ai/cli bootstrap\n```\n\nYou pick what to set up (a blank read-only credential, or a **blueprint**\nlike task tracking) and sign in once with a token from the\ndeveloper portal. The command then:\n\n- mints a scoped `ssk_*` for **this machine** (independently rotatable),\n- creates the matching AccessProfile — **data-plane only**; the command\n  refuses to provision control-plane scope (keys / profiles / billing / …),\n- backs up and merges the entry into `claude_desktop_config.json` (Claude\n  Desktop, Cursor, Cline). For **Claude Code**, add `--client code`: it merges\n  the project `.mcp.json` and prints the equivalent `claude mcp add` command.\n\nRestart your MCP client and you're done. It's idempotent (re-run any time);\n`--rotate` replaces this machine's key.\n\n**Want to browse the data yourself?** `bootstrap` sets up the key for your\n*agent*, not a login for *you* — so a blueprint's context won't appear in the\ndata-plane app's switcher until you join your own user to it (the app lists only\ncontexts your user has access in). Grant yourself a role once, either in the admin\napp (**Access → Contexts → _your context_ → Profiles → Create profile**, pick\nyourself from the by-email picker, choose a role — no raw id needed) or from the\nCLI with `--principal me` (resolves to your own user):\n\n```bash\nvectros access grant --principal me --context <context-id> --role <role>\n```\n\nBlueprints that ship a human role (e.g. `agentic-sdlc`'s `editor`) let you use\n`--role`; otherwise grant inline scopes with `--actions records:r,search:r,…`.\n\nFor scripted / agent use, set the sign-in token in the environment and skip\nthe prompts:\n\n```bash\nVECTROS_BOOTSTRAP_TOKEN=… npx -y @vectros-ai/cli bootstrap \\\n  --blueprint task-management --yes\n```\n\nPrefer to wire it up by hand? See **Configure manually** below.\n\n## Connect from your client\n\n| Client | One-click | Manual |\n|---|---|---|\n| **Claude Desktop** | [Desktop Extension (`.mcpb`)](https://github.com/vectros-ai/vectros-mcp-server/releases/latest/download/vectros.mcpb) — double-click, paste your key | [JSON snippet](#configure-manually-claude-desktop-or-any-mcp-client) |\n| **Cursor** | [![Add to Cursor](https://cursor.com/deeplink/mcp-install-dark.svg)](https://cursor.com/install-mcp?name=vectros&config=eyJjb21tYW5kIjoibnB4IiwiYXJncyI6WyIteSIsIkB2ZWN0cm9zLWFpL21jcC1zZXJ2ZXIiXSwiZW52Ijp7IlZFQ1RST1NfQVBJX0tFWSI6IiJ9fQ%3D%3D) | `.cursor/mcp.json`, same shape as below |\n| **VS Code** | [![Install in VS Code](https://img.shields.io/badge/VS_Code-Install-0098FF?logo=visualstudiocode&logoColor=white)](https://insiders.vscode.dev/redirect/mcp/install?name=vectros&config=%7B%22command%22%3A%22npx%22%2C%22args%22%3A%5B%22-y%22%2C%22%40vectros-ai%2Fmcp-server%22%5D%2C%22env%22%3A%7B%22VECTROS_API_KEY%22%3A%22%22%7D%7D) | `.vscode/mcp.json`, the same entry under a top-level `servers` key |\n| **Claude Code** | `claude mcp add` (below) | [project `.mcp.json`](#configure-manually-claude-code) |\n| **Cline / Continue** | — | same JSON snippet as Claude Desktop |\n| **Smithery** | `npx -y @smithery/cli install @vectros-ai/mcp-server` | — |\n| **Codex** | — | TOML snippet (below) |\n\nThe fastest path on **every** client is `npx -y @vectros-ai/cli bootstrap` — it\nmints a scoped key and writes the config for you. The one-click buttons install\nthe server entry; you then supply the key (bootstrap, or paste your `ssk_...`).\n\n**Codex** (`~/.codex/config.toml`):\n\n```toml\n[mcp_servers.vectros]\ncommand = \"npx\"\nargs = [\"-y\", \"@vectros-ai/mcp-server\"]\nenv = { VECTROS_API_KEY = \"ssk_live_...\" }\n```\n\n## Honest caveats\n\nPrecision is the pitch — what this server deliberately does *not* do:\n\n- **There's a human step.** Bootstrap needs a developer-portal sign-in / bridge\n  token. One command, but a person signs in — there is no fully unattended\n  provisioning.\n- **No web tools, on purpose.** The agent surface has no web-search or web-fetch\n  tools at all. Vectros is the memory, not the browser.\n- **Agent document upload is text-inline today.** An agent ingests document text\n  inline; on the stdio transport a jailed local-file upload is supported, but\n  bulk file upload from the agent surface isn't the path today.\n- **Audit history is tamper-*evident*, not tamper-proof.** A state-continuity\n  chain makes out-of-band alteration *detectable*; it is not continuous\n  automated verification.\n\n## Configure manually (Claude Desktop or any MCP client)\n\nIf `@vectros-ai/cli` is installed **globally** (`npm install -g @vectros-ai/cli`,\nnot a one-off `npx` run — the server needs `vectros` to still be on `PATH`\nlater, when IT runs, not just while bootstrap ran) and you've run\n`vectros bootstrap` with it, omit the `env` block entirely — the server\nresolves your key from the local `vectros` CLI keyring automatically (see\n[Credential resolution](#credential-resolution) below). `vectros login` alone\ndoes **not** do this — it stores a separate sign-in session, not this key —\nso `bootstrap` is the step that actually has to have run:\n\n```json\n{\n  \"mcpServers\": {\n    \"vectros\": {\n      \"command\": \"npx\",\n      \"args\": [\"-y\", \"@vectros-ai/mcp-server\"]\n    }\n  }\n}\n```\n\nNo CLI installed, or a machine you can't log in on? Set the key directly\ninstead:\n\n```json\n{\n  \"mcpServers\": {\n    \"vectros\": {\n      \"command\": \"npx\",\n      \"args\": [\"-y\", \"@vectros-ai/mcp-server\"],\n      \"env\": {\n        \"VECTROS_API_KEY\": \"ssk_live_...\"\n      }\n    }\n  }\n}\n```\n\nThis file lives under Claude Desktop's own per-user app-support directory,\nnot a shared repo — but a real key pasted into it is still a live secret at\nrest: don't paste it into a chat, ticket, or screenshot with the value\nintact, and prefer the keyring form above whenever you can.\n\nRestart Claude Desktop. The agent now sees the Vectros tools and\ntwo resources as callable surfaces.\n\n## Configure manually (Claude Code)\n\nClaude Code reads a project-scoped `.mcp.json` with the same shape.\n**Never commit a real key into it** — `.mcp.json` is exactly the kind of file\nteams check in to share a project's tooling, and a live `ssk_*`/`sk_*` value\ninside it is a credential leak the moment it lands in git history, not just\nif the repo is public.\n\nThe way to share this config safely: commit the entry with **no `env` block\nat all**, and let each developer's own `vectros` CLI keyring supply the key\n(see [Credential resolution](#credential-resolution) below — this is the\nsame delegation `git credential` / `docker-credential-*` use). This needs\neach teammate to have `@vectros-ai/cli` installed **globally** and to have\nrun `vectros bootstrap` with it — `npx`-ing the CLI once, or running\n`vectros login` alone (a separate sign-in session, not this key), leaves\nnothing on `PATH` or in the keyring for the server to find later:\n\n```json\n{\n  \"mcpServers\": {\n    \"vectros\": {\n      \"command\": \"npx\",\n      \"args\": [\"-y\", \"@vectros-ai/mcp-server\"]\n    }\n  }\n}\n```\n\nOr let Claude Code's CLI write that keyring-based entry for you:\n\n```bash\nclaude mcp add vectros -- npx -y @vectros-ai/mcp-server\n```\n\nIf a machine genuinely has no `vectros` CLI installed, you can pass the key\ndirectly with `-e VECTROS_API_KEY=ssk_live_...` — but then keep that config\n**local**: add `.mcp.json` to `.gitignore` first, rather than committing it\nwith the key inside.\n\nAdd `-e VECTROS_API_BASE_URL=<your environment's API base URL>` to point the server at a\ndifferent environment.\n\n**Load it into a session by restarting.** A Claude Code session that was\nalready open when you added the server won't pick it up mid-session — fully\nquit and reopen the project (not just re-select the tab). The `/mcp` panel\nshows the connector marketplace, not locally-configured stdio servers, so it\nwon't confirm the server is loaded — ask the agent to call a Vectros tool\ninstead. Config is keyed by the **git common root**, so a linked worktree\nresolves to its main repo's `.mcp.json` — add and open from the same project.\n\n> **Windows note:** if your `.npmrc` (or a global npm config) points the\n> `@vectros-ai` scope at another registry, a bare `npx -y @vectros-ai/mcp-server`\n> can resolve a build other than the public release. If the command above fails\n> to start, either remove the scoped-registry override for a plain `npx` run, or\n> pin an explicit version (`npx -y @vectros-ai/mcp-server@<version>`) known to\n> work.\n\n## Tools (23 tools)\n\n**Search & RAG**\n\n| Tool | What it does |\n|---|---|\n| `hybrid_search` | Hybrid BM25 + dense search across the tenant's indexed content (records + documents). Narrow by ownership (`scope` for one dimension, `scopeFilters` for several at once — e.g. one client within one org), folder, type, metadata filters, a created date window, and keyword-precision (`textMode`) / relevance floors. Returns the indexed projection of each hit. |\n| `rag_ask` | Ask a question grounded against the indexed corpus. Scope retrieval (ownership — `scope` or multi-dimension `scopeFilters` — / folder / type / metadata filters / date window) and steer generation (`instructions` / `temperature`). Streaming generation aggregated; progress notifications keep the call alive for the generation window. Optional `providerAlias` routes one call through your own model provider (see below). |\n| `document_ask` | Ask a question grounded against a single document. Same aggregation + progress-notification shape as `rag_ask`, including the optional `providerAlias`. |\n\n**Records** (structured, schema-validated data)\n\n| Tool | What it does |\n|---|---|\n| `list_schemas` | List the record-schema catalog the credential can see (filter by `surface` or resolve one by `recordType`). Makes `record_query` / `record_create` discoverable. |\n| `record_query` | Query records by lookup field — equality (`value`), range, or prefix, with `asc`/`desc` ordering and an optional `sortFrom`/`sortTo` window — or list mode, choosing one of `type`, `folderId` (every record in a folder, any type — combine with `type` to narrow), or `recent` (the account-wide recently-updated feed across all types), then optionally filtering the first two by ownership. Also supports composite equality across 2-3 fields (`values`), but only against a lookup the *schema* declares over those fields together (see `list_schemas`) — not any two fields you pick. |\n| `record_get` | Fetch one record by id, including its full payload (large payloads truncated to protect the agent context window). |\n| `record_batch_get` | Fetch several records by id (1-100) in one call, each with its full payload. Returns `missingIds` for any requested id you can't access, since the API silently omits them. |\n| `record_create` | Create a record of a given type; idempotent by `externalId`; optional per-record `indexMode`. |\n| `record_batch_write` | Create or upsert up to 50 records in one call, instead of N `record_create` round-trips. Items may mix types and are validated and scope-checked individually. `atomicity: all_or_nothing` commits them as one transaction (nothing is written if any item fails); the default `best_effort` writes each independently. Reports success whenever the batch was *processed* — read the per-item `results`, not just the absence of an error. |\n| `record_update` | Patch a record's payload (deep-merged; `null` deletes a key); optimistic concurrency via `expectedVersion`. |\n| `record_delete` | Permanently delete a record by id (leaves a tombstone). |\n\n**Documents** (text/file content, indexed for search + Q&A)\n\n| Tool | What it does |\n|---|---|\n| `document_ingest` | Create a document — inline text body OR local file upload (file mode is stdio-transport only). Idempotent by `externalId`; optional `schemaId` + `payload` for a typed, lookup-queryable document. An `externalId` with no `schemaId` is refused by platform 0.46.0 and later unless you also pass `confirmUntyped: true`. |\n| `document_query` | Query documents by lookup field (equality / range / prefix, with `asc`/`desc` ordering) or list mode (filter by folder and ownership). |\n| `document_get` | Fetch a document by id (metadata incl. lifecycle `status` + processing `indexStatus`; optional text truncated at ~8K tokens; optional presigned `downloadUrl` for file-backed documents — always forces a download, never inline rendering, regardless of file type). |\n| `document_update` | Patch a document's metadata / typed payload (deep-merged); archive/restore via `status` (`ARCHIVED` soft-retracts from search, `ACTIVE` restores); optimistic concurrency via `expectedVersion`. |\n| `document_delete` | Permanently delete a document by id (removes it and its indexed content). |\n\n**Folders** (group records + documents)\n\n| Tool | What it does |\n|---|---|\n| `folder_query` | Get a folder by id, or list folders (a parent's children for tree navigation, or a flat tenant list; paginated via `nextCursor`). |\n| `folder_create` | Create a folder. |\n| `folder_update` | Update a folder's name / description / ownership (merge-patch; optimistic concurrency via `expectedVersion`; folders cannot be re-parented). |\n| `folder_delete` | Delete a folder. It must be empty first — no documents, no records, and no sub-folders — and a context root is protected outright. |\n\n**Identity & history**\n\n| Tool | What it does |\n|---|---|\n| `current_identity` | Describe the credential: tenantId, environment, principalType, principalKeyId, principalLabel, and (for scoped credentials) allowedActions + dataScope. Does **not** yet include `granted_capabilities` (`member-lifecycle` / `forensic-read` / `context-directory-read` / `delegate-mint`, as of API 0.40.0, joined by `delegate-principal-stamp` in 0.42.0 and `trigger-control-plane-grant` in 0.44.0) — a separate reach dimension a scope clause can carry that `/v1/ping` doesn't report yet, so allowedActions + dataScope may understate a credential's true reach. Also reports this server's own version and the bundled SDK version (`mcpServerVersion`, `sdkVersion`). |\n| `lookup_principal` | Resolve a user, or an identity entity in a namespace (`org`/`client`/any namespace you registered), by your own `externalId` (→ its Vectros UUID, for the ownership filters) or by a schema lookup field. Pass `contextId` to target a specific app context for a context-owned namespace. Read-only. |\n| `version_history` | Read the audit/version trail (CREATE/UPDATE/DELETE, with actor + diff) for one record or document. Read-only. |\n\nAll 23 tools wrap published Vectros HTTP API endpoints. JSON\nresponses are what the agent sees as tool output. Per-call cost\nsurfaces via the `usage` field on inference responses.\n\n### Routing a call through your own model provider\n\n`rag_ask` and `document_ask` take an optional `providerAlias`: the alias of a model provider config your Vectros\naccount has activated. When you pass it, that one call is served by your own provider instead of the\nplatform-hosted default, and `model` then names a model on your provider's own id space (it falls back to that\nprovider config's default model when omitted). The server forwards `providerAlias` only when you supply it and\nnever fills it in.\n\nIt works only after your account has set up the provider and signed the platform's risk-acceptance waiver. Without\nboth, the platform refuses the call with a `403`, which the tool returns to you as written. A call served by your\nown provider leaves the platform-hosted Bedrock path, and Vectros's AWS BAA boundary, so decide deliberately whether a given call should use it.\nNothing here is a statement about how a provider you chose handles your data.\n\n### Opting into a subset\n\nPass `VECTROS_MCP_TOOLS=hybrid_search,rag_ask` to register only those\ntwo — useful for giving an agent read-only search access without\nexposing ingestion or inference costs to the credential. Unknown tool\nnames fail fast at startup.\n\n## Resources\n\nTwo read-only resources for ambient context (no tool call required):\n\n| URI | What it returns |\n|---|---|\n| `vectros://schemas` | Same payload as `list_schemas`. Lets the agent preload schemas into context for ambient discovery. |\n| `vectros://identity` | Same payload as `current_identity`. Lets the agent self-describe without spending a tool call. |\n\n## Recommended credential\n\nUse a **scoped permanent API key** (`ssk_*`), not a root key (`sk_*`).\n\nA scoped key is bound to a narrowed `AccessProfile` — e.g. read-only\nacross one org scope (`scope:org`). If your MCP install is compromised, the blast\nradius is whatever the profile allows, not the whole tenant. The\nserver emits a `warn` log line on startup when you pass a wildcard\n`sk_*` for exactly this reason.\n\n**The easiest way to get one is `npx -y @vectros-ai/cli bootstrap` (above)**\n— it mints a least-privilege `ssk_*` and an AccessProfile for you, no root\nkey required. To do it by hand instead: mint a scoped key from the developer\nportal under **Keys → Create scoped key**, bind it to an AccessProfile\ntitled `mcp-read-all` or `mcp-read-scoped`, and drop the resulting\n`ssk_live_...` into the config above.\n\nSee the Vectros developer documentation on scoped tokens (\"Recommended\nAccessProfile for MCP\") for least-privilege credential setup — the\n`vectros bootstrap` flow provisions a scoped `ssk_*` key and its AccessProfile\nin one command.\n\n> **A root `sk_*` can no longer file into another app context, as of API 0.43.0.**\n> If you run this server on a root key and a tool call names a `folderId` /\n> `parentFolderId` — or a `schemaId` on a document — belonging to a context other\n> than `default`, it is now refused with a uniform `400 \"Folder not found\"` /\n> `\"Schema not found\"`. This affects `document_ingest`, `document_update`,\n> `record_create`, `record_update` and `folder_create`, and it is a change in\n> outcome: those calls used to succeed. They never did what they appeared to,\n> though — a root key's writes are always stamped `default`, so the row landed in\n> `default` while its folder or schema lived elsewhere, permanently invisible to\n> the context that owned them. Existing rows written the old way are untouched and\n> still readable, updatable and deletable. The fix is the same scoped key\n> recommended above: one bound to the target context can file into it and always\n> could.\n\n## Credential resolution\n\nThe server resolves its API key from the first source that yields one:\n\n1. **`VECTROS_API_KEY`** — always wins when set.\n2. **The `vectros` CLI keyring** — if the key is unset and\n   [`@vectros-ai/cli`](https://www.npmjs.com/package/@vectros-ai/cli) **0.9.0+** is on\n   your `PATH`, the server runs `vectros keyring show --format raw` as a subprocess\n   and uses the key it prints. By default that is your **active** identity; set\n   `VECTROS_KEYRING_ALIAS` to pick a specific entry. This is the same pattern as\n   `git credential` / `docker-credential-*` / `aws credential_process`: the key\n   lives in one place, and the server, your scripts, and your agent hooks all read\n   it from there instead of each keeping a plaintext copy that drifts.\n3. **Neither** — startup fails with a message naming both options.\n\nThe resolved key is held in memory and never logged. Startup logs which alias it\nresolved (not the key), so you can tell at a glance which identity the server is\nrunning as — `vectros keyring doctor` shows the same view.\n\n> **Startup warns when it picks an identity you didn't name.** If `VECTROS_API_KEY`\n> is unset and no `VECTROS_KEYRING_ALIAS` is set, the server falls back to your\n> **active** keyring entry and logs a warning — it is running as whatever identity\n> `vectros switch` last selected, which may be a `ssk_live_*` key acting on real data\n> or a `ssk_test_*` one that isn't. Either can be an unwelcome surprise, because a\n> blank placeholder (`\"VECTROS_API_KEY\": \"\"` in a client config, or `-e VECTROS_API_KEY`\n> passing through an unset var in Docker) reads as \"not configured yet\" but resolves\n> like an unset key. Nothing is blocked — name an entry with `VECTROS_KEYRING_ALIAS`,\n> or set `VECTROS_API_KEY`, and the warning goes away. `vectros keyring doctor` shows\n> which entry is active and which of your keys are live.\n\n## Environment variables\n\n| Var | Required | Default | Purpose |\n|---|---|---|---|\n| `VECTROS_API_KEY` | no\\* | — | Vectros API key. Accepts `sk_*` / `ssk_*` / `st_*`; `ssk_*` recommended. \\*Required **unless** the `vectros` CLI is installed with a usable keyring entry — see [Credential resolution](#credential-resolution). Takes precedence when set. |\n| `VECTROS_KEYRING_ALIAS` | no | (the active entry) | Resolve this `vectros` keyring entry instead of the active one. Ignored when `VECTROS_API_KEY` is set. |\n| `VECTROS_API_BASE_URL` | no | `https://api.vectros.ai` | Override for another environment. Validated: must be `https://` (or `http://` to localhost) and an official `*.vectros.ai` host. |\n| `VECTROS_ALLOW_INSECURE_BASE_URL` | no | — | Set `1` to bypass the base-URL allow-list (e.g. a trusted local proxy). **Not recommended** — sends your key to an unvalidated host; logs a warning. |\n| `VECTROS_MCP_INGEST_ROOT` | no | process cwd | Directory `document_ingest`'s `filePath` mode is jailed to. Paths escaping it (traversal/absolute/symlink) or matching a sensitive pattern are rejected. |\n| `VECTROS_MCP_TOOLS` | no | (all tools) | Comma-separated tool names (e.g. `hybrid_search,rag_ask`). |\n| `VECTROS_MCP_DEBUG` | no | — | Set `1` for verbose stderr logs. |\n| `VECTROS_MCP_SKIP_PING_VALIDATION` | no | — | Set `1` to disable the startup `/v1/ping` check. |\n| `VECTROS_MCP_HTTP_PORT` | HTTP only | `8765` | Port for HTTP transport. |\n| `VECTROS_MCP_HTTP_HOST` | HTTP only | `127.0.0.1` | Bind address. Use `0.0.0.0` for all interfaces (then set a bearer token). |\n| `VECTROS_MCP_HTTP_BEARER_TOKEN` | HTTP only | — | Client→server bearer token. **Strongly recommended** beyond localhost; **required** for a non-loopback bind. |\n| `VECTROS_MCP_HTTP_ALLOWED_HOSTS` | HTTP only | — | Comma-separated extra `Host` values to allow (DNS-rebinding protection). Set to the public hostname(s) behind a reverse proxy. |\n| `VECTROS_MCP_HTTP_ALLOWED_ORIGINS` | HTTP only | — | Comma-separated extra `Origin` values to allow. |\n| `VECTROS_MCP_HTTP_ALLOW_INSECURE` | HTTP only | — | Set `1` to permit a non-loopback bind without a bearer token. **Not recommended.** |\n\n## Startup credential validation\n\nBefore the first tool call, the server runs a `GET /v1/ping` check\nagainst your credential. Bad keys fail at startup with a clear\nerror instead of opaquely 401'ing mid-conversation. Set\n`VECTROS_MCP_SKIP_PING_VALIDATION=1` to disable.\n\n## HTTP transport\n\nFor hosted-MCP scenarios — running the server behind a network\nboundary, sharing it across multiple agent instances, deploying as\na sidecar — the package also ships an HTTP binary:\n\n```bash\nVECTROS_API_KEY=ssk_live_... \\\nVECTROS_MCP_HTTP_PORT=8765 \\\nVECTROS_MCP_HTTP_BEARER_TOKEN=$(openssl rand -hex 32) \\\n  npx -y -p @vectros-ai/mcp-server vectros-mcp-server-http\n```\n\n> The HTTP binary is **not** the default — select it explicitly with\n> `npx -p <pkg> vectros-mcp-server-http`. A bare `npx -y @vectros-ai/mcp-server`\n> always starts the stdio server.\n\nThe server listens on `http://127.0.0.1:8765/mcp` by default. The\nbearer token is optional but **strongly recommended for any\ndeployment beyond localhost** — without it, anyone who can reach the\nport can call Vectros with your credentials.\n\nHealth probe lives at `GET /healthz` (always unauthenticated, k8s\nreadiness-friendly).\n\nCurrent limitation: the server uses one upstream credential per process\n(the key resolved at startup). Per-request credential override via the\nincoming Authorization header is a planned enhancement. For now, deploy one\nserver per credential boundary you want.\n\n## Programmatic use (advanced)\n\nMost consumers use the CLI shape above. If you need to embed the\nserver in your own Node process:\n\n```ts\nimport { VectrosMCPServer, createStdioTransport } from '@vectros-ai/mcp-server';\n\nconst server = new VectrosMCPServer({\n  apiKey: process.env.VECTROS_API_KEY!,\n  tools: ['hybrid_search', 'rag_ask'],\n  resources: ['schemas'],     // opt-in resource filter; default = all\n  validateOnStart: true,      // default — set false to skip startup ping\n});\nawait server.connect(createStdioTransport());\n```\n\n## What this server deliberately doesn't expose\n\nThis is a decision, not a backlog. An MCP server is a tool surface handed to an\nautonomous caller, so a capability the API offers is not automatically a tool —\neach one has to earn its place on an agent's surface.\n\nThe line is the **data plane**: records, documents, folders and search are here in\nfull. Anything that grants or administers authority is not, and neither is the\ndesign-time layer that defines the data model.\n\n- **Stored scripts** (`/v1/scripts` — push, list, fetch, delete). A stored script is\n  code, not data. Authoring it is a design-time act, the same reason schema mutation\n  lives in the CLI rather than here: an agent that can write the code that later runs\n  under your credential is a different proposition from one that can write records.\n- **Synchronous script execution** (`POST /v1/scripts/execute`, the `scripts:x` scope).\n  The closer call of the two, and excluded on operational grounds rather than reach —\n  a `scripts:x:<name>` grant is a deliberately narrow, per-script permission, and an\n  ordinary scoped key can hold it. What an agent handles badly is the failure surface:\n  a run whose outcome cannot be determined returns `500 EXECUTION_OUTCOME_UNKNOWN` with\n  writes that may or may not have committed, which is not something a caller resolves\n  by retrying — it has to go and look. Getting a retry right also means reusing an\n  `Idempotency-Key` across attempts, and a tool call has no natural retry identity, so\n  an agent re-invoking after a timeout would silently run the script a second time.\n  Exposing this well needs a deliberate design for those two things, not a thin wrapper.\n  Until then, run scripts from a caller that can handle them — the API, the SDK, or the\n  CLI.\n- **Trigger rules** (`/v1/triggers`). Declaring a rule grants authority — a rule's\n  `scopes`/`roleIds` are live, and declaring one is scope-monotonicity-checked like\n  any other authority-granting surface. Minting authority is not an agent action.\n- **Trigger failure history** (`GET /v1/trigger-failures`) and **usage/billing**\n  (`GET /v1/usage`). Both are read-only, and both are operational rather than\n  data-plane — they describe how your automation and your account are behaving, not\n  what your content says. That is a question for the developer portal or the CLI,\n  where a person is looking at it, rather than a tool an agent reaches for mid-task.\n- **Identity, access and credential administration** — users, access profiles,\n  roles, app contexts, issuer registrations, and scoped-key minting. Unchanged\n  since launch: identity CRUD stays off the agent tool surface by design.\n  `lookup_principal` resolves an identifier to an id and does nothing else.\n- **Compliance operations** (erasure, export). Same reason.\n\nIf one of these belongs on your agent's surface, that's worth telling us — the\nline is drawn on purpose and can be redrawn with a reason.\n\n## What this server doesn't do (yet)\n\n- **No prompts capability** — `/rag` and `/ingest_pdf` slash-command\n  templates land in a future release. (Provisioning — the `bootstrap` command — lives\n  in the separate [`@vectros-ai/cli`](https://www.npmjs.com/package/@vectros-ai/cli)\n  package, above.)\n- **HTTP transport is single-tenant per process** — per-request\n  credential override via incoming Authorization header is a v1.0+\n  enhancement.\n- **No Python implementation** — TS only. Python users can `npx`\n  this server from any project.\n- **`rag_ask` and `document_ask` are not natively streaming** —\n  full answer aggregated before the tool returns. Progress\n  notifications cover the latency. Native MCP-spec streaming lands\n  when the spec stabilizes.\n\nThe server is on a pre-1.0 track toward a stable 1.0 release.\n\n## Rate limits\n\nTool calls hit the same per-minute rate limits as any API client; the\n[rate limits guide](https://docs.vectros.ai/guides/operations-trust/rate-limits) says which requests count. On a `429` the server surfaces the error with its\n`Retry-After` hint so the agent can pace and retry rather than blind-retrying. The guide also lists\nthe per-plan limits.\n\n## Building from source\n\n```sh\ngit clone https://github.com/vectros-ai/vectros-mcp-server\ncd vectros-mcp-server\nnpm install\nnpm run build\nnpm test\n```\n\n`npm install` pulls `@vectros-ai/sdk` from the configured npm\nregistry.\n\n`npm run build` runs `tsup` to produce the dual ESM/CJS output in\n`dist/`. The SDK is bundled into the build (see\n[`tsup.config.ts`](./tsup.config.ts)) — the published npm package is\nself-contained and works without `.npmrc` config on the consumer's\nmachine.\n\n## Security & trust\n\nVectros enforces per-customer, fail-closed isolation and least-privilege scoped keys, with a\ntamper-evident audit and version history. Customer-facing surfaces are hardened through extensive\nadversarial security review. For the full trust posture, drawn plainly with its boundaries, see the\n[compliance and trust guide](https://docs.vectros.ai/guides/operations-trust/compliance).\n\n**Tool output is untrusted, API-supplied content.** Every tool here returns your own tenant's data —\ndocument text, search results, error messages — as plain text inside the MCP response. This server\ndoes not sanitize, escape, or pre-render that text, and none of these tools evaluate or execute it.\nRender tool output the same way you'd render any other data an agent pulled from an external source\n— safely, in your client — rather than `eval`-ing it or trusting it as pre-sanitized.\n\n## License\n\nApache-2.0. See the LICENSE file.\n","readmeFilename":"README.md"}