M
MCP Directory CURATED DIRECTORY
911 MCP servers indexed
中文
← Back to directory
COMPARE UP TO 4 SERVERS

Compare MCP servers

Compare scores, permissions, risks, and fit in one decision-focused table.

Dimensionllmwiki MCP ServerCompile raw sources into an auditable, interlinked knowledge base.MartinLoop MCP ServerAn independent control layer that gives AI coding agents budgets, brakes, and receipts
FMRS57 / 100 · C79 / 100 · B
Reliability8 / 2012 / 20
Security and permissions12 / 2018 / 20
Maintenance12 / 2016 / 20
Documentation15 / 2018 / 20
Setup experience10 / 2015 / 20
Best for
  • Research material that benefits from review, provenance, and reuse
  • Codebase documentation, team handbooks, standards, design notes, and decision logs
  • Agent workflows that precompile knowledge before querying it
  • Engineering teams scaling AI coding agents while controlling spend
  • Platform teams that need auditable, rollback-aware agent execution records
  • Organizations using multiple agents (Claude, Codex, Gemini) under one governed flow
Not for
  • High-churn log streams where raw search is sufficient
  • General-purpose static-site generation
  • Heavy ontology databases
  • Developers who just want a simple code-completion helper without run governance
  • Teams unwilling to accept local JSONL run records with HMAC signing
  • Environments without a supported adapter (Claude/Codex/Gemini CLIs, direct provider, or verifier-only)
Required permissions
  • Access to the selected knowledge-base project and its sources, wiki, and .llmwiki data
  • Appropriate network access when ingesting web pages or using external connectors; the README does not specify connector permissions
  • Provider credentials at call time for LLM-backed operations
  • Read/write access to the configured repo root (writable scope restrictable via --allow-path/--deny-path)
  • Ability to invoke the chosen agent CLI (Claude/Codex/Gemini, etc.) and its underlying model account
  • Local disk writes for run records, receipts, and share outputs (share/run-receipt., etc.)
  • Execution of user-configured verifier commands (e.g. npm test)
Risks and side effects
  • LLM-generated content may contain confidence, contradiction, provenance, or freshness issues
  • External OKF imports enter the review queue by default, but explicitly trusted imports can write to the active knowledge base
  • Ingest, connector, import, and other write operations can change project data; review, lint, and eval should be used
  • The README does not specify an MCP transport or client configuration, so client compatibility cannot be assumed
  • Verifier commands are executed; poorly chosen verifier commands carry security risk despite preflight policy checks
  • Cost and token figures may be estimates (labeled with provenance) and should not be treated as settled accounting
  • Receipt integrity must be verified before use as trustworthy evidence; missing rollback evidence is flagged as EVIDENCE_BOUNDARY
  • Policy defaults come from martin.config.yaml and can be overridden by CLI flags; misconfiguration can loosen safety boundaries
Supported clientsClaude Code, Codex, Gemini CLI, Cursor, VS Code, GitHub Copilot, Continue
Tools20