token-context-mcp
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- AlicenseNot gradedqualityBmaintenanceEnables AI coding agents to retrieve token-budgeted project context, search code symbols, look up definitions, and access project memory and cross-project learnings through local MCP tools. It reduces redundant exploration by supplying the smallest useful context from a deterministic, local-first index.MIT
- AlicenseNot gradedqualityAmaintenanceEnables AI coding agents to query a codebase as a knowledge graph, providing token-budgeted context, search, and impact analysis via MCP tools.MIT
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to locally search, query, and understand codebases with token-efficient context, dependency graphs, history, architecture diagrams, and metrics through MCP.14 npm3MIT
- AlicenseNot gradedqualityAmaintenanceA read-only MCP tool that provides local-first, source-backed repository context for coding agents, returning metadata and a bounded read plan without requiring full file reads.14 npmMIT
- AlicenseNot gradedqualityBmaintenanceEnables coding agents to retrieve compact, cited repository maps through MCP tools such as search, symbol inspection, flow investigation, and deep context loading.Apache 2.0
- AlicenseNot gradedqualityAmaintenanceEnables AI coding agents to retrieve repository context through stdio-based MCP tools, including ranked repo maps, context packs, and live symbol search.17 npmMIT
TDQS
Scored across 9 tools
Each tool targets a distinct capability—repo enumeration, context maps, symbol lookup, impact slices, index freshness, imports, FTS search, file skeletons, and symbol packets—though find_symbols/search_source and get_impact_slice/get_module_dependents sit close enough that an agent may need careful descriptions. Overall boundaries are clear and the descriptions reinforce purpose.
The set mostly follows a get_<object> pattern with list_repositories, find_symbols, and search_source as reasonable verb variations. All names are snake_case and consistently place the action before the object, creating a predictable surface.
Nine tools is appropriate for a token-context indexing server: each tool covers a distinct aspect of repository context without redundancy. The count feels neither thin nor overloaded.
The surface covers the full workflow: list available repositories, fetch orientation maps, search for symbols and source text, inspect imports and file skeletons, check index freshness, and retrieve bounded context packets. A raw full-file read tool is intentionally absent given the bounded-context purpose, but this is a reasonable design choice rather than a gap.