mcp-intelligence-context
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- AlicenseNot gradedqualityBmaintenanceProvides token-efficient code retrieval for coding agents by indexing repositories and enabling ranked snippet search, symbol outlines, and surgical line reads.MIT
- AlicenseNot gradedqualityAmaintenanceIndexes a codebase into a symbol-level graph and exposes tools for finding symbols, querying relationships, and assessing impact, letting AI coding agents answer structural questions in a single call within a token budget.1,076 npm3Apache 2.0

Semantic Code Search MCPofficial
FlicenseNot gradedqualityDmaintenanceProvides AI coding agents with structured access to indexed codebases via semantic search, symbol analysis, and file reading tools.12-- FlicenseNot gradedqualityAmaintenanceProvides efficient code navigation and graph-based analysis for AI agents, enabling symbol resolution, callers, implementations, and type schemas with minimal token usage.-
- AlicenseNot gradedqualityBmaintenanceEnables LLM agents to efficiently understand and navigate a codebase by providing semantic search over symbols and a reference graph, replacing expensive grep/glob calls with structured tools like definition lookup, caller/callee queries, and change-impact analysis.2MIT
- AlicenseNot gradedqualityDmaintenanceProvides semantic codebase understanding via a graph, enabling AI agents to search, explore, and plan changes with whole-repo context in a single tool call.33MIT
TDQS
Scored across 6 tools
Each tool has a largely distinct purpose (index, overview, search, file details, dependencies, context), and the descriptive text flags get_relevant_context as the main entry point. However, search_code and get_relevant_context could both serve as the starting point for a 'find X' request, creating minor selection ambiguity.
All tools follow a consistent verb_noun snake_case pattern (index_, get_, search_), making the API predictable and scannable. The only minor nitpick is abbreviating 'repository' as 'repo' in get_repo_overview, but this does not affect the overall pattern.
Six tools sit at the sweet spot for a code-intelligence server, each earning its place in the index-query workflow. The set covers setup, orientation, discovery, drill-down, and impact analysis without bloat.
The core indexing-to-context pipeline is well covered, including re-indexing via refresh and reverse-dependency analysis for safe edits. Minor gaps exist (no full-file body reader, no way to list indexed repositories or explicitly purge the cache), but these seem like intentional scope decisions for a token-budget-focused tool.