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"An overview of knowledge graphs" matching MCP servers:

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    Enables token-efficient semantic search and analysis over any directory of files through hybrid search, directory overview, structural analysis, and dependency graphs.
    14
    MIT
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    An experimental MCP server that compresses git commit co-change coupling graphs using the Baligács temporal clique linear spanner algorithm, reducing edge and token counts by ~55-65% while preserving temporal reachability, and exposes tools like index_repository, get_architecture, search_code, and temporal_compress for querying code knowledge graphs.
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    An MCP server that maps any repository into architecture diagrams, providing tools for scanning code facts, building import graphs, and generating Mermaid/DOT diagrams, plus architecture rule enforcement for CI.
    5
    303
    MIT
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    Indexes a mono-repo into a knowledge graph and provides MCP tools to query code structure—packages, components, routes, HTTP calls—without file reads or grep round-trips.
    7
    22
    MIT
  • A
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    Enterprise-grade (40m+ lines) codebase intelligence in a zero-setup, private and local MCP: managed indexing, hybrid semantic search, polyglot code dependency graphs, and DB/API/infra knowledge. Benchmark: 61% less tokens, 84% fewer calls, 37x faster than standard AI grep.
    25
    3,749
    3,247
    AGPL 3.0
  • A
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    Provides deep structural analysis of Python source code via AST, including function signatures, call graphs, cyclomatic complexity, code smells, dead code detection, and protocol conformance.
    20
    MIT
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    An MCP server that indexes TypeScript/JavaScript codebases into precise call and import graphs using the TypeScript compiler API, allowing Claude or any MCP client to query definitions, callers, callees, and perform impact analysis.
    7
    MIT
  • A
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    Hybrid MCP server that combines Graphify’s structural code graphs with Understand-Anything’s semantic knowledge bases, exposing both as MCP tools for code analysis and natural-language questioning.
    10
    MIT
  • A
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    quality
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    maintenance
    Enables storing and querying structured information about software code entities (classes, functions, files) and their relationships (calls, imports) along with qualitative observations like design decisions and change rationale.
    9
    19
    4
    MIT
  • A
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    Enables AI assistants and developers to analyze code for language-specific best practices and idiomatic patterns across programming languages, CI automation, and configuration formats.
    16
    2
    MIT
  • A
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    Knowledge graph for token-efficient code reviews. Builds a structural map of your codebase with Tree-sitter, tracks changes incrementally, and gives AI agents precise context via MCP tools. Features fixed multi-word search, qualified call resolution, dual-mode embedding (ONNX local + LiteLLM cloud), and output pagination.
    7
    64
    Apache 2.0