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search your screen recordings and audio transcriptions","maintainers":[{"name":"louis030195","email":"louis.beaumont@gmail.com"}],"readme":"# Screenpipe MCP Server\n\n<a href=\"https://www.pulsemcp.com/servers/screenpipe-screenpipe\"><img src=\"https://www.pulsemcp.com/badge/top-pick/screenpipe-screenpipe\" width=\"400\" alt=\"PulseMCP Badge\"></a>\n\n<br/>\n\nhttps://github.com/user-attachments/assets/7466a689-7703-4f0b-b3e1-b1cb9ed70cff\n\nMCP server for screenpipe - search your screen recordings, audio transcriptions, and control your computer with AI.\n\n## Usage attribution\n\nWhen Screenpipe analytics are enabled, successful nonempty retrievals produce\n`qualified_value_event` with `surface` (`api` or `mcp`) and `agent_client`.\nSupported app identifiers are `claude`, `chatgpt`, `codex`, `cursor`, `gemini`,\n`openclaw`, `hermes`, `runner`, `windsurf`, `vscode`, `grok`, and `grokbot`. Claude Desktop\nand Claude Code share the existing `claude` bucket. This identifies the caller,\nnot the app appearing in a recording.\n\nMCP uses `SCREENPIPE_MCP_CLIENT` when it names a supported app, falling back to\nthe initialization handshake's client name. HTTP sessions resolve independently.\nOnly the fixed identifier is forwarded; raw client names are never analytics\nproperties. Unrecognized MCP clients remain `unknown`.\n\nInstalled REST skills send `X-Screenpipe-Client: api` and a fixed\n`X-Screenpipe-Agent` header for their target app. Other API clients can send the\nsame headers. Missing or unrecognized app identifiers retain the legacy\n`direct_api` bucket on qualified-value events. `search_performed` also includes\nthe fixed `agent_client` (`unknown` when unidentified), alongside `request_source`.\nThese are self-reported identifiers, not verified app identities; copied skills\nand callers that omit the headers cannot be reliably attributed. Historical\ngeneric API events cannot be assigned an app retroactively.\n\nAttribution adds fields to existing events and uses the existing analytics\nopt-out. It does not scan running apps or send prompts, search text, or raw\nclient names. HTTP MCP now reports successful searches through the same\nbest-effort local telemetry endpoint as stdio MCP; empty/failed searches do not\nproduce qualified-value events.\n\n## Installable plugins\n\nBuild the local Claude Desktop extension and the cloud plugin from source:\n\n```sh\ncd packages/screenpipe-mcp\nbun install --frozen-lockfile\nbun run build:installers\n```\n\n- `installers/screenpipe-local.mcpb`: open in Claude Desktop's extension installer.\n  Bundles the server and its dependencies; Claude supplies Node. Keep Screenpipe\n  running. Includes an optional sensitive API key setting and API URL setting.\n- `installers/screenpipe-cloud.zip`: portable remote plugin with OpenAI/Codex and\n  Claude compatibility manifests. Requires Data Sync and OAuth sign-in; exposes\n  only synced device listing and search. See the [cloud setup guide](plugins/screenpipe-cloud/README.md).\n- `installers/SUBMISSION.md`: listing copy, endpoint, permissions guidance, and\n  acceptance cases for directory submission. Building does not publish a listing.\n\nThe archive builder uses an explicit file allowlist, so local environment files,\ncredentials, development dependencies, and source tests are not packaged.\n\n## Installation\n\n### Option 1: The screenpipe desktop app (Recommended)\n\nThe most reliable setup is to install the [screenpipe desktop app](https://screenpi.pe)\nand connect Claude Desktop from **Settings → Connections** (or during onboarding).\nThis writes a config that:\n\n- uses the **bundled `bun`** shipped with the app (an absolute path — no Node/`npx`\n  or `PATH` dependency, and ~3× faster cold start), and\n- injects your **`SCREENPIPE_LOCAL_API_KEY`** into the server's `env`, so the MCP\n  authenticates instantly instead of running slow key discovery at startup.\n\nBoth matter: a config without the key forces the server to discover it via\nsubprocess fallbacks, which on a cold package cache can stall Claude Desktop's MCP\nstartup and produce `Could not attach to MCP server screenpipe`.\n\n### Option 2: Manual NPX (no desktop app)\n\nIf you're not using the desktop app, edit your Claude Desktop config:\n\n- **macOS**: `~/Library/Application Support/Claude/claude_desktop_config.json`\n- **Windows**: `%AppData%\\Claude\\claude_desktop_config.json`\n\n```json\n{\n  \"mcpServers\": {\n    \"screenpipe\": {\n      \"command\": \"npx\",\n      \"args\": [\"-y\", \"screenpipe-mcp@latest\"],\n      \"env\": {\n        \"SCREENPIPE_LOCAL_API_KEY\": \"sp-…\"\n      }\n    }\n  }\n}\n```\n\nRequires Node/`npx` on `PATH`. Pin `@latest` so the first install doesn't cache a\nstale version forever. Get your key with `screenpipe auth token`. If you omit the\nkey, the server will try to discover it through the bundled Screenpipe CLI and\nthen `npx`. It never opens the live SQLite database directly. Discovery can be\nslower on first run, so setting the environment variable is still recommended.\n\nEnterprise admins: add `SCREENPIPE_ENTERPRISE_TOKEN` (and, for orgs running their\nown query gateway, `SCREENPIPE_TEAM_API_URL`) to the same `env` block to get the\n`team-*` tools — see [Enterprise team tools](#enterprise-team-tools-team-).\n\n### Option 3: HTTP Server (Remote / Network Access)\n\nThe MCP server can run over HTTP using the [Streamable HTTP transport](https://modelcontextprotocol.io/specification/2025-03-26/basic/transports#streamable-http), allowing remote MCP clients to connect over the network instead of stdio. This is ideal when your AI assistant (e.g., OpenClaw) runs on a different machine than screenpipe.\n\n```bash\n# loopback only (default)\nnpx -y screenpipe-mcp --http --port 3031\n\n# expose to your LAN with bearer auth\nnpx -y screenpipe-mcp --http --listen-on-lan --api-key $(openssl rand -hex 16)\n\n# or from source — must build first so dist/ exists\nbun install && bun run build\nbun run start:http -- --port 3031\n```\n\n> Tip: `npx screenpipe-mcp-http` (without `--http`) does **not** work —\n> npm resolves by package name, and there is no `screenpipe-mcp-http`\n> package. The HTTP server ships as a transport inside the\n> `screenpipe-mcp` package; use `--http` as shown above, or invoke the\n> bin directly with `npx -p screenpipe-mcp screenpipe-mcp-http`.\n\nThe server exposes:\n- **MCP endpoint**: `http://localhost:3031/mcp` — Streamable HTTP transport (POST for requests, GET for SSE stream)\n- **Health check**: `http://localhost:3031/health` — always unauthenticated, for monitors\n\n**Options:**\n| Flag | Description | Default |\n|------|-------------|---------|\n| `--port` | Port for the MCP HTTP server | `3031` |\n| `--screenpipe-port` | Port where screenpipe API is running | `3030` |\n| `--listen-on-lan` | Bind `0.0.0.0` so other devices on the LAN can connect. Requires `--api-key`. | off (binds `127.0.0.1`) |\n| `--api-key <secret>` | Bearer token required for non-loopback requests (`Authorization: Bearer <secret>`). Loopback always allowed. | none |\n\nWhen the Screenpipe API requires authentication, set `SCREENPIPE_LOCAL_API_KEY`\nin the HTTP server's environment (`SCREENPIPE_API_KEY` is the fallback). Obtain\nit with `screenpipe auth token`, and keep it out of client configuration and\nchat. The server uses this key for upstream API requests, including retrieval\ntelemetry. `--api-key` is a separate credential for callers connecting to MCP;\nit is never forwarded to the Screenpipe API.\n\n```bash\nSCREENPIPE_LOCAL_API_KEY=\"$(screenpipe auth token)\" npx -y screenpipe-mcp --http\n```\n\n**Connecting a remote MCP client:**\n\nPoint any MCP client that supports HTTP transport at the `/mcp` endpoint:\n\n```json\n{\n  \"mcpServers\": {\n    \"screenpipe\": {\n      \"url\": \"http://<your-ip>:3031/mcp\",\n      \"headers\": {\n        \"Authorization\": \"Bearer <your-secret>\"\n      }\n    }\n  }\n}\n```\n\nIf your machines are on different networks, expose port 3031 via Tailscale, SSH tunnel, or similar — see the [OpenClaw integration guide](https://docs.screenpi.pe/openclaw) for detailed examples.\n\n> **Note:** The HTTP server currently exposes `search_content` only. The stdio server has the full tool set (export-video, list-meetings, activity-summary, search-elements, frame-context). We're working on bringing HTTP to full parity.\n\n### Option 4: From Source\n\nClone and build from source:\n\n```bash\ngit clone https://github.com/screenpipe/screenpipe\ncd screenpipe/packages/screenpipe-mcp\nbun install\nbun run build\n```\n\nThen configure Claude Desktop:\n\n```json\n{\n  \"mcpServers\": {\n    \"screenpipe\": {\n      \"command\": \"node\",\n      \"args\": [\"/absolute/path/to/screenpipe-mcp/dist/index.js\"]\n    }\n  }\n}\n```\n\n**Note:** Restart Claude Desktop after making changes.\n\n## Enterprise team tools (`team-*`)\n\n`team-search`, `team-devices`, `team-records`, and `team-frame` query your whole\norg instead of just this machine. They are registered **only** when an enterprise\nadmin token is present, and they need **two** independent settings: a token, and\nthe base URL of the API that token is valid for.\n\n### 1. The token\n\nAn `sk_ent_…` enterprise admin token, resolved in this order:\n\n1. `SCREENPIPE_ENTERPRISE_TOKEN` env var (MCP config, terminal)\n2. `team_api_token` in `~/.screenpipe/enterprise.json` — written by the desktop\n   app's **Settings → Privacy → Admin Team API Token**\n\nNo token → the `team-*` tools do not appear at all.\n\nThe MCP rereads `enterprise.json` for each team request, so replacing or clearing\nthe saved token takes effect without restarting it. An explicit\n`SCREENPIPE_ENTERPRISE_TOKEN` still takes priority. If that override expires,\nreplace it or remove it to use the desktop app's saved token, then restart the\nMCP server to reload its environment.\n\n### 2. The base URL\n\n| Priority | Where | Example |\n|---|---|---|\n| 1 | `--team-api-url` flag | `npx -y screenpipe-mcp --team-api-url https://sp-gw.acme.internal/api/enterprise/v1` |\n| 2 | `SCREENPIPE_TEAM_API_URL` env var | `SCREENPIPE_TEAM_API_URL=https://sp-gw.acme.internal/api/enterprise/v1` |\n| 3 | `gateway_url` in `~/.screenpipe/enterprise.json` | `{ \"gateway_url\": \"https://sp-gw.acme.internal/api/enterprise/v1\" }` |\n| 4 | *(default)* the hosted control plane | `https://screenpi.pe/api/enterprise/v1` |\n\nTrailing slashes are trimmed, so both `…/v1` and `…/v1/` work.\n\n**If your org runs its own query gateway, you must set this.** On the write-only\narchive tier your telemetry never reaches the hosted API — it lands in your own\nobject storage and is served by a gateway inside your network. The hosted API has\nno read path to that data, so leaving the default in place makes every `team-*`\ncall fail with **HTTP 401**, even though the tools show up and the token is valid.\nThe bearer token is the same either way; only the base URL moves.\n\nFull Claude Desktop config for a gateway org:\n\n```json\n{\n  \"mcpServers\": {\n    \"screenpipe\": {\n      \"command\": \"npx\",\n      \"args\": [\"-y\", \"screenpipe-mcp@latest\"],\n      \"env\": {\n        \"SCREENPIPE_LOCAL_API_KEY\": \"sp-…\",\n        \"SCREENPIPE_ENTERPRISE_TOKEN\": \"sk_ent_…\",\n        \"SCREENPIPE_TEAM_API_URL\": \"https://sp-gw.acme.internal/api/enterprise/v1\"\n      }\n    }\n  }\n}\n```\n\nVerify which base a running server picked up by asking for `team-devices` — the\nerror text on a missing token also prints the base currently in use.\n\n### Known limits\n\n- **Requires `screenpipe-mcp` >= 0.19.0.** `0.18.15` and earlier hardcode the\n  hosted base and cannot be repointed at a gateway at all. Check with\n  `npm view screenpipe-mcp version`, or read `serverInfo.version` from the MCP\n  `initialize` response.\n- Priority 3 is populated by the desktop app, which writes `gateway_url` from\n  the org's policy poll. It needs an admin signed in on that machine; on a\n  server or CI box use the env var or the flag.\n- The HTTP transport (`--http`) exposes `search_content` only; `team-*` tools are\n  stdio-only.\n- The `.mcpb` bundle (Claude Desktop extension install) has no UI for these\n  variables — use the manual NPX config above for gateway orgs.\n\n## Testing\n\nTest with MCP Inspector:\n\n```bash\nnpx @modelcontextprotocol/inspector npx screenpipe-mcp\n```\n\n## Transport Modes\n\n| Mode | Command | Use Case |\n|------|---------|----------|\n| **stdio** (default) | `npx screenpipe-mcp` | Claude Desktop, local MCP clients |\n| **HTTP** | `npx screenpipe-mcp --http` | Remote clients, network access, OpenClaw on VPS |\n\n## Available Tools\n\n### search-content\nSearch through recorded content with content type filtering:\n- `all` — OCR + Audio + Accessibility (default)\n- `ocr` — Screen text from screenshots\n- `audio` — Audio transcriptions\n- `input` — User actions (clicks, keystrokes, clipboard, app switches)\n- `accessibility` — Accessibility tree text\n- `parsed` — Compact app-specific messages, emails, tasks, documents, and code review (experimental; may be empty when parsing is disabled or unsupported)\n- Time range, app/window, and speaker filtering\n- Parsed data can also be filtered by `frame_id` or resolved `actor_id`\n- Pagination support\n\n### export-video\nExport screen recordings as video files:\n- Specify time range with start/end times\n- Configurable FPS for output video\n\n### activity-summary\nGet a lightweight compressed activity overview for a time range:\n- Authoritative total active minutes and server data status\n- Per-app active minutes and a bounded window/tab breakdown\n- Edited document paths plus an optional bounded parsed-context sample for identifying tasks\n- Recent accessibility text and audio context\n\nUse active-minute fields for duration. Edited paths, parsed rows, frames, text,\nand audio samples are supporting context only; their counts are not time.\nParsed capture is experimental and may be disabled or unsupported; the base\nactivity summary remains complete without it.\n\n### list-meetings\nList detected meetings with id, duration, app, attendees, and note snippet. Pass `q` to filter by substring (title, attendees, notes) — `q` searches all meeting history, so omit the time range when looking for a person or topic. Follow up with `get-meeting` (optionally `include_transcript: true`) for the full note and speaker-attributed transcript.\n\n### search-elements\nSearch structured UI elements (accessibility tree nodes and OCR text blocks):\n- Filter by source, role, app, time range\n- Much lighter than search-content for targeted UI lookups\n- Returns a compact `outline` view by default — a deduped, indented tree of the\n  text-bearing nodes (`#id` refs, `(off-screen)` flags), ~91% fewer tokens than\n  raw element JSON\n- Pass `purpose: \"automation\"` for automation targeting context with response-local\n  refs, best-effort stable keys, state, bounds, and allowed actions. Refresh it\n  before each action; historical database ids are not live control handles.\n  `computer-use` remains a legacy alias.\n- If `purpose` is omitted, the MCP follows the desktop `AI context use` setting.\n  The backward-compatible default remains the read/memory outline.\n\n### get-frame-elements\nThe whole element tree for one frame, as the same compact outline. Pass\n`purpose: \"automation\"` for the automation targeting view.\n\n### frame-context\nGet accessibility text, parsed tree nodes, and extracted URLs for a specific frame.\n\n### keyword-search\nFast FTS5 keyword search across OCR + audio combined. Returns matches with `frame_id`, app, timestamp, and text positions.\n\n### list-meetings / get-meeting / update-meeting / start-meeting / stop-meeting\nManage the meeting store. `list-meetings` filters by substring; `get-meeting` returns title/attendees/times/full note (add `include_transcript: true` for the speaker-attributed transcript). `update-meeting` writes only the fields you pass. `start-meeting` and `stop-meeting` drive manual meeting recording sessions.\n\n### search-speakers / list-unnamed-speakers / update-speaker / merge-speakers\nSpeaker identification workflow. Search by name prefix, list speakers that haven't been named yet, rename a speaker, or merge two speakers when the same person was detected as different ones.\n\n### add-tags\nTag a screen frame (vision) or audio chunk (audio) so it can be retrieved later.\n\n### update-memory\nCreate, update, or delete a persistent memory (facts, preferences, decisions the user wants to remember).\n\n### send-notification\nSend a notification to the screenpipe desktop UI.\n\n### control-recording\nStart or stop audio recording. This does not pause or resume screen capture.\n\n### health-check\nCheck if screenpipe is running and healthy. Returns recording status, frame/audio stats, and timestamps.\n\n### list-audio-devices\nList available audio input/output devices for recording.\n\n### list-monitors\nList available monitors/screens for capture.\n\n### list-pipes / create-pipe / run-pipe / pipe-logs\nManage pipes — scheduled AI automations that run a markdown prompt on a schedule (e.g. \"every day at 9am\"). `list-pipes` shows enabled state + schedule; `create-pipe` creates one; `run-pipe` triggers a one-off test run; `pipe-logs` fetches recent execution output.\n\n### team-search / team-devices / team-records / team-frame\nTeam-tier tools, registered only when an enterprise admin token is configured. `team-search` runs substring search across the entire org's telemetry, `team-devices` lists enrolled devices (hostname, OS), `team-records` dumps chronological frame, parsed-app, or audio data for a time window, and `team-frame` returns one bounded PII-redacted JPEG using IDs from search or records. Orgs running their own query gateway must also set `SCREENPIPE_TEAM_API_URL` — see [Enterprise team tools](#enterprise-team-tools-team-) for the full precedence order.\n\n## Example Queries in Claude\n\n- \"Search for any mentions of 'rust' in my screen recordings\"\n- \"Find audio transcriptions from the last hour\"\n- \"Show me what was on my screen in VSCode yesterday\"\n- \"Export a video of my screen from 2-3pm today\"\n- \"Find what John said in our meeting about the database\"\n- \"What did I type in Slack today?\" (uses content_type=input)\n- \"What did I copy to clipboard recently?\" (uses content_type=input)\n- \"Show me accessibility text from Chrome\" (uses content_type=accessibility)\n\n## Requirements\n\n- screenpipe must be running on localhost:3030\n- Node.js >= 18.0.0\n\n## Notes\n\n- All timestamps are handled in UTC\n- Results are formatted for readability in Claude's interface\n- macOS automation features require accessibility permissions\n- The MCP tools already return compact, readable text (the element tools follow the desktop capture profile unless the caller sets a purpose). If you instead call the underlying screenpipe REST API directly (e.g. via `curl`), the list endpoints (`/search`, `/elements`, `/frames/{id}/elements`) accept `?format=csv|tsv` for a columnar table (column names written once) and `?fields=a,b,c` to select only the columns you need (dotted paths like `content.text`); the element endpoints also accept `?format=outline` (~91% fewer tokens than JSON) or `?format=automation` for fresh refs, best-effort keys, actions, state, and bounds. On list-shaped results that is a 70–91% token cut versus the default JSON, which stays unchanged when no param is set.\n\n## Privacy Policy\n\nThe Screenpipe MCP server is a local-only bridge between Claude and your\nlocal Screenpipe instance. It does not collect, transmit, or store tool\nresults, recordings, OCR text, audio transcripts, screenshots, or UI events\non its own.\n\n### What this MCP server does\nWhen Claude invokes a tool (`search-content`, `activity-summary`, etc.)\nthe MCP server forwards the request to `http://localhost:3030` — the\nScreenpipe daemon running on your machine — and returns the response.\nThat's the entire data path.\n\n### Data collection\nThe MCP server sends privacy-preserving crash and error reports to Screenpipe's\nSentry project so we can diagnose startup failures like \"server disconnected\"\nor \"could not attach to MCP server\". These reports include the MCP package\nversion, runtime, transport mode, and sanitized exception details. They do not\ninclude tool arguments, tool results, screen content, audio, transcripts,\nscreenshots, API tokens, or your home-directory path.\n\nTo disable crash/error reporting, set any of:\n`SCREENPIPE_MCP_SENTRY_DISABLED=1`, `SCREENPIPE_TELEMETRY_DISABLED=1`, or\n`SCREENPIPE_DISABLE_TELEMETRY=1` in the MCP launch environment.\n\n### Data usage\nTool calls are passed straight through to your local Screenpipe daemon\nand the results stream back to Claude. The MCP server doesn't keep\nanything. Database access stays inside Screenpipe's daemon and first-party CLI,\nwhich own SQLite lifecycle and locking; the MCP server never opens, copies, or\nmutates the live database, WAL, or shared-memory files. Use MCP tools such as\n`query_recordings` for SQL-shaped analysis.\n\n### Data storage\nNothing is stored by the MCP server itself. Recordings, OCR text,\naudio transcripts, and UI events are stored by the Screenpipe app in a\nSQLite database under `~/.screenpipe/` on your device. Retention is\nwhatever you configure inside the Screenpipe app — typically you\ncontrol it via the storage settings panel.\n\n### Third-party sharing\nThe MCP server talks to `localhost:3030` for tool calls and to Screenpipe's\nSentry project for sanitized crash/error reports unless disabled as above.\nIt does not contact Anthropic or send recorded content to Screenpipe's servers.\nIf you choose to enable optional cloud features inside the Screenpipe\napp itself (e.g. cloud sync, cloud AI), those are governed by the\nScreenpipe app's privacy policy, not this MCP server's data flow.\n\n### Retention\nThe MCP server has no persistent state. The data your Screenpipe app\ncaptures is retained according to your Screenpipe storage configuration\nand is deletable at any time (`rm -rf ~/.screenpipe` removes everything).\n\n### Source code\nThe Screenpipe MCP server is source-available under the Screenpipe\nCommercial License and the entire source is public at\n<https://github.com/screenpipe/screenpipe/tree/main/packages/screenpipe-mcp>.\nEvery line is auditable.\n\n### Contact\nQuestions or concerns: open an issue at\n<https://github.com/screenpipe/screenpipe/issues> or reach out via\n<https://screenpi.pe>.\n\n## Saved personal workflows\n\n`list-workflows` searches the desktop Workflows catalog; `get-workflow` returns\nordered steps, gaps and historical accessibility evidence through the same\nauthenticated API. Both tools are available in stdio and HTTP modes. The running\ndesktop engine must support `/workflows`; an older engine returns an error.\nConnected clients can use this context to plan automation, but retrieval neither\nauthorizes nor executes actions. Captured bounds/IDs must be resolved again in\nthe live app. Missing or expired capture and approximate frame matches are explicit.\nNo automatic upload to ChatGPT, Claude or other services is introduced.\n\nThe API exposes `GET /workflows?q=...&limit=20&offset=0` and\n`GET /workflows/{id}?include_automation=true` in OpenAPI. Workflow IDs derive from\ntitle, trigger and outcome, so rediscover after a rename. Results omit embedded\nscreenshot bytes. Detail includes up to 30 stages and 100 context nodes per frame,\nwith explicit truncation. `frame-context` with `purpose=\"automation\"`,\n`node_offset` and `node_limit` (maximum 500) retrieves further nodes while preserving\nroles, normalized monitor bounds, automation IDs, state and structural ancestors.\nThe default reading mode is unchanged. `get-frame-elements` with\n`purpose=\"automation\"` remains the compact targeting view.\n\nA workflow's frame ID and timestamp must match the current recorder before node\nhydration. Missing, expired or mismatched frames remain explicit. A historical\ncontrol is not proof it was clicked: the action target remains unknown until an\nagent establishes it from current context and the user's instructions.\n\nThe API uses the desktop owner's configured app-local `workflows/catalog.json`\nwith its validated backup, rather than guessing another installation's path.\nUnconfigured or unreadable storage returns 503. Existing authentication, vault\nlocking and history access apply. Data-scoped or privacy-filtered pipes are denied\nrather than receiving an unfiltered synthesized report; explicit frame endpoint\ndenials also apply when hydrating accessibility nodes.\n\n```text\nDesktop catalog -> authenticated /workflows -> MCP list-workflows / get-workflow\n                          |\n                          +-> existing frame metadata/context APIs\n                          +-> bundled API skill and generated skill references\n```\n\nEach stage can also return `inputSearch` arguments for `search-content` with\n`content_type=\"input\"`. Input results preserve recorded x/y, keys/modifiers,\nelement role/name and linked frame IDs. Treat the bounded time window as\ncandidate events to verify, not as automatic proof of the workflow's actions.\n","readmeFilename":"README.md"}