sw-dev-knowledge-base-mcp
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- AlicenseNot gradedqualityDmaintenanceProvides direct access to local documentation files through simple search and overview tools, enabling LLMs to query project-specific markdown documentation without requiring vector databases or RAG pipelines.MIT
- AlicenseNot gradedqualityDmaintenanceProvides AI assistants with direct access to local Markdown documentation libraries, enabling them to list, read, and search through docs on demand.MIT
- AlicenseAqualityAmaintenanceEnables AI agents to search local Markdown documents using natural language, with automatic indexing and section-level retrieval.105 npm1MIT
- AlicenseAqualityCmaintenanceEnables AI assistants to search, retrieve, and browse Markdown documentation in a local folder, then answer questions with cited sources.6MIT
- AlicenseAqualityAmaintenanceEnables AI agents to discover, read, search, and install Markdown-based knowledge (rules, skills, workflows) from a local directory via MCP tools.129 npmMIT
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to search, read, and traverse a local knowledge base of Markdown files using full-text search and relationship graph, reducing token usage.MIT
TDQS
Scored across 4 tools
Each tool has a clearly distinct role: grep_docs searches file contents, read_doc retrieves exact file ranges, list_docs enumerates the directory structure, and kb_status reports corpus and layer metadata. The tools complement each other with explicit cross-references, so an agent should not confuse them.
Three tools use a predictable verb_noun snake_case pattern (grep_docs, read_doc, list_docs), but doc vs docs is inconsistent and kb_status breaks the verb pattern by using an abbreviation plus noun. The naming is still readable and easy to guess overall.
Four tools is a well-scoped count for a read-only knowledge base MCP: list, grep, read, and status each cover a necessary part of the workflow. There are no redundant tools and no obvious missing core operation.
The tool surface fully covers the read-only domain: agents can discover paths with list_docs, check layer availability with kb_status, locate matches with grep_docs, and retrieve exact citable content with read_doc. Write operations are not part of the stated purpose, so no lifecycle gap exists.