About agentscore
agentscore is an MCP security service for evaluating MCP packages and dependencies. Its tools provide package scans, trust verdicts, repository checks, incident exposure lookups, and setup for GitHub Actions policy enforcement.
Key features
- 01Scan packages for security findings
- 02Return allow, warn, or block verdicts
- 03Inspect repository MCP dependencies
- 04Generate or install CI policy workflows
- 05Check exposure and abuse reports
- 06View monitoring status and scan history
Use cases
- 01Assess an MCP package before installation
- 02Review MCP dependencies in a repository
- 03Find servers affected by a compromised dependency
- 04Add package policy checks to GitHub Actions
MCP support
The MCP server exposes eight tools for scanning and assessing package trust, inspecting repository dependencies, setting up policy gates, and checking exposure, abuse reports, and monitoring.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
8Saved tool list · updated 2w ago
| Parameter | Type | Required | Description |
|---|---|---|---|
| npm | string | Yes | npm package name (e.g. 'exa-mcp-server', '@modelcontextprotocol/server-github') |
Details
From the project README@agentscore-xyz/mcp-server
MCP security trust layer. Scan packages, get trust verdicts, inspect repo-wide MCP dependencies, generate Policy Gate setup, install the CI workflow directly, check incident exposure, and query the abuse database. Eight tools for MCP security decisions. No API key, zero config.
Scan any MCP package for security issues: agentscores.xyz
Quick Start
Claude Desktop
Add to your claude_desktop_config.json:
{
"mcpServers": {
"agentscore": {
"command": "npx",
"args": ["-y", "@agentscore-xyz/mcp-server"]
}
}
}
Cursor / Any MCP Client
npx @agentscore-xyz/mcp-server
What This Does
Your AI can now make security decisions about MCP packages:
You: "Is exa-mcp-server safe to install?"
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."
You: "The axios package was compromised. Which MCP servers are affected?"
Claude: calls check_exposure "Multiple monitored MCP servers depend on axios, including exa-mcp-server, tavily-mcp, and figma-mcp."
You: "Scan @azure-devops/mcp for security issues"
Claude: calls scan_package "Score 75/100, MODERATE risk. Found: preinstall script modifying npm registry config. No provenance attestations."
You: "Check this repo for MCP dependencies"
Claude: calls check_my_repo "MCP dependencies found: 5. Two are warnings. Run generate_policy_gate_setup to turn these checks into a CI gate."
You: "Set up AgentScore Policy Gate for this repo"
Claude: calls install_policy_gate "The workflow file is written to
.github/workflows/agentscore-policy-gate.yml. Commit and push. GitHub OIDC will auto-provision the repo on first run."
Available Tools
| Tool | What it does |
|---|---|
scan_package | Full security scan: install scripts, prompt injection, source code patterns, provenance posture, MCP tool extraction |
get_verdict | Trust decision: allow, warn, or block based on scan findings. Also reports monitoring status and publisher posture. |
check_my_repo | Inspect the current repo for MCP dependencies and summarise verdicts for every package detected locally. |
generate_policy_gate_setup | Generate the exact OIDC-based GitHub Actions workflow needed to enforce Policy Gate in CI. |
install_policy_gate | Write .github/workflows/agentscore-policy-gate.yml directly into the repo so the gate is ready to commit. |
check_exposure | Incident response: which monitored MCP servers depend on a given package? |
check_abuse | Query the KYA abuse database for reported packages or agents |
monitor_status | Check if a package is under continuous monitoring and get scan history |
From Ad-Hoc Scans To CI Enforcement
The MCP server now bridges one-off package checks into the sticky product:
- Run
check_my_repoto see every MCP package used in a repo. - Run
generate_policy_gate_setupto preview the OIDC-based GitHub Actions workflow. - Run
install_policy_gateto write the workflow file directly into the repo. - Commit and push. The first run auto-provisions through GitHub OIDC.
That turns "is this package safe?" into "this repo now enforces MCP dependency policy on every PR."
Risk Levels
| Score | Risk | Meaning |
|---|---|---|
| 85-100 | LOW | Clean or minor issues only |
| 70-84 | MODERATE | Some findings, review recommended |
| 50-69 | ELEVATED | Significant findings, use with caution |
| 30-49 | HIGH | Serious issues, not recommended |
| 0-29 | CRITICAL | Do not use |
What the Scanner Checks
- Install scripts (postinstall/preinstall hooks with network calls or code execution)
- Prompt injection patterns in package metadata
- Suspicious URLs (sketchy TLDs, ngrok, raw IPs)
- Source code patterns (command injection, unsafe eval, hardcoded secrets)
- Publisher provenance (trusted publishing, attestations)
- Dependency count and metadata completeness
- MCP tool definitions extracted from published source
Monitoring
AgentScore continuously monitors hundreds of MCP packages. The check_exposure and monitor_status tools use this live dataset. When a package like axios gets compromised, you can instantly find which MCP servers are affected.
Links
- Website: agentscores.xyz
- API Docs: agentscores.xyz/docs
- Methodology: agentscores.xyz/methodology
Licence
MIT
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.