agent-kb
Related Servers
Alternatives to agent-kb
No user-submitted related servers found.
Related Servers
- FlicenseNot gradedqualityDmaintenanceAn in-memory knowledge graph MCP server that gives coding agents structural and semantic recall over codebases by indexing Python source, ADR documents, and project configuration, exposing 7 tools for search, traversal, context retrieval, and natural-language Q&A.-
- AlicenseNot gradedqualityBmaintenanceProvides LLM agents with a structured, queryable, local-first knowledge base with typed documents and full-text search via MCP.MIT
- AlicenseCqualityBmaintenanceLocal-first codebase intelligence engine providing AI coding agents with a typed MCP toolset for understanding and navigating code repositories.10051Apache 2.0
- AlicenseNot gradedqualityDmaintenancePersistent codebase knowledge layer for AI agents. Pre-digests codebases into structured knowledge (symbols, dependency graphs, co-change patterns, architectural decisions) and serves via MCP. 28 languages, 14 tools, ~85% token reduction.12 npm8MIT
- AlicenseNot gradedqualityCmaintenanceA local MCP server that parses codebases into semantic chunks, indexes them in SQLite with vector embeddings, and exposes MCP tools for LLM agents to query.MIT
- AlicenseCqualityAmaintenanceLocal-first MCP server that turns project documentation and source code into durable, evidence-backed context for AI agents, with bounded retrieval and explicit gap reporting.8112 npmApache 2.0
TDQS
Scored across 4 tools
Each tool targets a distinct operation: search, fetch-by-id, list sources, and reindex. There is no meaningful overlap; kb_search and kb_get are clearly separated by query-based retrieval versus direct ID lookup.
All tools use the consistent kb_ prefix followed by a clear verb or verb-noun phrase: search, get, list_sources, reindex. The naming pattern is uniform and predictable.
Four tools is compact but well-scoped for a knowledge base server covering retrieval, inspection, source listing, and maintenance. Each tool earns its place without unnecessary redundancy.
Core knowledge base operations are covered: search, fetch chunk content, list sources, and reindex. Minor gaps exist such as no delete/clear collection or detailed status beyond source listing, but these are not critical for the apparent purpose.