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Most users have no way to ask, mid-conversation, \"is this package safe?\" before they wire it into their agent. This server makes that question askable directly inside the same chat where you discover the package.\n\nIt is the **machine-readable trust layer** behind agentscores.xyz, packaged as an MCP server so any agent can consume it.\n\n## Quick start\n\n### Claude Desktop\n\nAdd to your `claude_desktop_config.json`:\n\n```json\n{\n  \"mcpServers\": {\n    \"agentscore\": {\n      \"command\": \"npx\",\n      \"args\": [\"-y\", \"@agentscore-xyz/mcp-server\"]\n    }\n  }\n}\n```\n\n### Cursor / VS Code / any MCP client\n\n```bash\nnpx @agentscore-xyz/mcp-server\n```\n\n## What you can ask\n\nThe primary use case: trust questions about packages, answered in conversation.\n\n> **You:** \"Is exa-mcp-server safe to install?\"\n>\n> **Claude:** *calls get_verdict* \"Verdict: ALLOW. Score 90/100, LOW risk. No provenance attestations (published by personal account). 9 tools exposed including web_search_exa and crawling_exa.\"\n\n> **You:** \"Scan @azure-devops/mcp for security issues.\"\n>\n> **Claude:** *calls scan_package* \"Score 75/100, MODERATE risk. Found: preinstall script modifying npm registry config. No provenance attestations.\"\n\n> **You:** \"The axios package was compromised. Which MCP servers depend on it?\"\n>\n> **Claude:** *calls check_exposure* \"Multiple monitored MCP servers depend on axios, including exa-mcp-server, tavily-mcp, and figma-mcp.\"\n\n> **You:** \"Is fa-mcp-sdk monitored? What is its history?\"\n>\n> **Claude:** *calls monitor_status* \"Yes, under continuous monitoring. Latest scan: HIGH risk. Republished 15+ times since the April 25 disclosure with no maintainer engagement on the open issues.\"\n\nThe agent picks the right tool. You ask the question the way you would ask a colleague.\n\n## CI enforcement (optional, section 2)\n\nIf you want the same trust data as a merge-time policy gate rather than an in-conversation question, the same MCP server can scaffold a GitHub Actions workflow for you.\n\n> **You:** \"Check this repo for MCP dependencies and set up a policy gate.\"\n>\n> **Claude:** *calls check_my_repo, then install_policy_gate* \"Found 5 MCP packages in your repo. Workflow written to `.github/workflows/agentscore-policy-gate.yml`. Commit, push, and the first PR will provision the gate via GitHub OIDC.\"\n\nThree tools support that flow:\n\n- `check_my_repo` — inspect the current repo's MCP dependencies.\n- `generate_policy_gate_setup` — preview the OIDC-based GitHub Actions workflow.\n- `install_policy_gate` — write `.github/workflows/agentscore-policy-gate.yml` directly into the repo.\n\nThe gate is the same data, just at a different point in the lifecycle. The primary surface is still the question.\n\n## Available tools\n\n| Tool | Question it answers |\n|------|---------------------|\n| `scan_package` | What does the live scan of this package look like, including install scripts, source patterns, capability surface, and findings? |\n| `get_verdict` | Should I allow, warn, or block this package? |\n| `check_exposure` | Which monitored MCP servers depend on a given package? (Incident response.) |\n| `monitor_status` | Is this package under continuous monitoring? What is its scan history? |\n| `check_abuse` | Has this package been reported in the KYA abuse database? |\n| `check_my_repo` | Inspect the current repo for MCP dependencies and summarise verdicts. |\n| `generate_policy_gate_setup` | Preview the OIDC-based GitHub Actions workflow for CI enforcement. |\n| `install_policy_gate` | Write the workflow file directly into `.github/workflows/`. |\n\n## Risk levels\n\n| Score | Risk | Meaning |\n|-------|------|---------|\n| 85-100 | LOW | Clean or minor issues only |\n| 70-84 | MODERATE | Some findings, review recommended |\n| 50-69 | ELEVATED | Significant findings, use with caution |\n| 30-49 | HIGH | Serious issues, not recommended |\n| 0-29 | CRITICAL | Do not use |\n\n## What the scanner checks\n\n- Install scripts (postinstall/preinstall hooks with network calls or code execution)\n- Prompt injection patterns in package metadata\n- Suspicious URLs (sketchy TLDs, ngrok, raw IPs)\n- Source code patterns (command injection, unsafe eval, hardcoded secrets) with context-aware mitigators\n- Publisher provenance (trusted publishing, attestations)\n- Dependency count and metadata completeness\n- MCP tool definitions extracted from published source\n\nThe scanner changelog and false-positive mitigator lineage are public at [agentscores.xyz/scanner/precision](https://agentscores.xyz/scanner/precision). Findings get corrected when maintainers raise valid false-positive challenges. The correction history is part of the record, not buried.\n\n## Continuous monitoring\n\nAgentScore monitors 1,600+ MCP packages on npm. `check_exposure` and `monitor_status` query this live dataset. When a package like axios gets compromised, you can ask mid-conversation which of your MCP servers are affected.\n\n## Links\n\n- **Live data:** [agentscores.xyz](https://agentscores.xyz)\n- **Per-package reports:** [agentscores.xyz/report/<package>](https://agentscores.xyz/report)\n- **Advisory feed:** [agentscores.xyz/security/advisories](https://agentscores.xyz/security/advisories) (also RSS)\n- **API docs:** [agentscores.xyz/docs](https://agentscores.xyz/docs)\n- **Methodology:** [agentscores.xyz/methodology](https://agentscores.xyz/methodology)\n- **Scanner precision changelog:** [agentscores.xyz/scanner/precision](https://agentscores.xyz/scanner/precision)\n- **Embed a badge:** [agentscores.xyz/badge](https://agentscores.xyz/badge)\n\n## Licence\n\nMIT\n","readmeFilename":"README.md"}