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MCP ServerL4high risk

GitHub MCP Server

Connect agents to GitHub repositories, issues, pull requests, and code search.

RepositoryDocs
Curated baseline · 52

A curated public baseline; every entry carries a verification level and risk labels. 25 from the automated pipeline

66
Recommended
Confidence: medium
80
Benchmark
Confidence: medium
Needs human reviewL4 · Seed profile normalized into AgentMaps schema.
Why
Recommendation 66, fits Coding, setup is medium.
Best for
Developers using Self-hosted for coding workflows.
Not for
Production write access without sandboxing or human approval.
Boundary
Verified to L4; still review permissions and output quality in your environment.
Remaining risk
High-risk permissions require explicit user approval and sandboxing.
Next step
Review tokens, write access, and network scope in a sandbox before team adoption.
Review before adoption
This capability includes high-risk, token, write, shell, or auth-gated gaps. L4 means interface parsing, not production safety approval.

What it is good for

Connect agents to GitHub repositories, issues, pull requests, and code search. AgentMaps treats this as a mcp server candidate and scores it with a capped benchmark score plus a separate recommendation score that includes trust, platform fit, setup preference, and risk preference.

Use cases

  • - Review code changes
  • - Inspect repository context
  • - Generate implementation notes
  • - Run repeatable task flows
  • - Coordinate tool calls

Best for

  • - Developers using Self-hosted for coding workflows.
  • - Teams that want visible setup, verification, and risk evidence before adoption.

Not for

  • - Production write access without sandboxing or human approval.
  • - Users who cannot provide the required credentials.

Limitations

  • - Scenario-level L5-L7 benchmark testing is not part of the current MVP record.
AI-native runtime contractTool/runtime connector

Runtime pattern before adoption

AI may help filter, explain, and draft a trial plan, but must not perform write, shell, external side effects, or production publishing before review.

Visible states

  • Collect task context and platform constraints
  • Preview setup, source, and permission boundaries
  • Trial in a sandbox or low-permission environment
  • Wait for human review before continuing

User controls

  • Revise task/platform filters
  • Add to Compare
  • Open source for review
  • Cancel high-risk adoption
  • Submit pending/staging evidence

Approval gates

  • Token/API key scope approval
  • Approval before writes or state mutation
  • External network target approval
  • Auth-gated path not fully tested

Failure recovery

  • Auth path needs manual reproduction or a constrained test account.

Trial acceptance

  • Can a user find a task-fit candidate within two minutes
  • Can the UI explain why it is recommended and where it does not fit
  • Can the user identify token, write, shell, network, or local file risk
  • Can the user separate L1/L2 evidence from full runtime proof
  • Does a failed trial have fallback or manual takeover

Verification evidence

The matrix shows passed, partial, skipped, and not-tested boundaries. It is not production adoption approval.

L1 Metadata

Source, docs, license, or package metadata exists.

passed
L2 Static audit

Static review assigns permission and risk boundaries.

passed
L3 Install path

Install path can be checked, but not necessarily in your environment.

passed
L4 Interface

Interface or entrypoint parsed; not a production safety approval.

passed
  • Seed profile normalized into AgentMaps schema.
  • Source and documentation fields are present.
  • Static risk flags are assigned.
  • Install path is represented for harness checks.
  • Interface metadata is represented for parser checks.
  • Benchmark score capped at 88 by L4 verification.

Trust profile

Heuristic estimate
Needs reviewstaticTrigger risk medium

Risk findings

  • - Requires Token
  • - Write Permission
  • - External Network

Verified evidence

  • - Seed profile normalized into AgentMaps schema.
  • - Source and documentation fields are present.
  • - Static risk flags are assigned.
  • - Install path is represented for harness checks.

Score breakdown

Safety43
Execution proxy90
Maintenance88
Setup83
Interface95
Standards89
Task fit86
Portability91

Why it scores well

  • - Clear task fit for the selected scenario.
  • - Static verification evidence is available.
  • - Portable across multiple AI clients.

Watch outs

  • - Requires credentials before full testing.
  • - High-risk permissions need sandboxing.

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