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524,366 tools. Updated 2026-09-06 15:15

"Code Review Graph Visualization Tools and Resources" matching MCP tools:

  • Get a transaction's graph structure for visualization and relationship analysis. Input protocol and hash to receive detailed transaction data.
    AGPL 3.0
  • Adjust graph visualization parameters like point size and edge influence to customize how network data appears in Graphistry MCP visualizations.
    MIT
  • Retrieve details about a stored graph visualization from Graphistry MCP to access and analyze network data properties.
    MIT
  • Export the current repository's behavioral graph as JSON for downstream analysis or visualization. Includes all code nodes, dependency and invocation edges, with each node colored by semantic workflow domain.
    MIT
  • Visualize project dependencies in a 3D interactive graph. Filter by file type, focus on file neighborhoods, and inspect or open files in VS Code.
    MIT

Matching MCP Servers

  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables AI coding assistants to query a persistent local code graph for targeted context, blast-radius analysis, and incremental updates, so they read only relevant files during reviews and large-repo workflows.
    MIT
  • A
    license
    A
    quality
    A
    maintenance
    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
    66
    Apache 2.0

Matching MCP Connectors

  • Corporate travel: search and book flights, hotels, rail and transfers, manage orders.

  • A skeptical senior-engineer code reviewer over MCP: risk-scans unified diffs, flags AI-generated-code tells, reports complexity hotspots, scans for leaked secrets, and runs an OWASP security pass — real analyzers, no external APIs. Free tier, no signup.

  • Check the current state of the gnaws server to see loaded resources, graph size, and available actions. Use this first to discover which tools you can call.
    AGPL 3.0
  • Generate an interactive HTML visualization of knowledge cards and their wiki-links as a graph. Open the file in a browser to explore relationships between concepts.
    MIT
  • Scan an AWS account with a profile to build a live graph of resources and relationships, enabling detection of unused resources and exports.
    AGPL 3.0
  • Visualize code architecture and detect duplicate code in one call: generate UML diagrams, call/dependency graphs, and knowledge graph exports, plus identify near-duplicate code segments.
    MIT
  • Analyze changed symbols against the code graph to identify transitive callers, test associations, and graph gaps. Use before refactor or PR review; run jambavan_index first.
    MIT
  • Retrieve the relay configuration URL for better-code-review-graph, opening it in the browser when possible. Returns the URL, launch status, and current status.
    Apache 2.0
  • Export the knowledge graph to an interactive HTML file so humans can visually inspect it. Get the output path and graph counts.
    Apache 2.0
  • Plan which discovered tools and code-graph capabilities can satisfy a given goal, returning the tool IDs to invoke. Maps natural language goals to actionable tool sequences.
    MIT
  • Dump the entire graph structure to Mermaid, JSON, or Graphviz DOT for visualization, enabling quick debugging and clear understanding of relationships.
    MIT
  • Generate a static HTML visualization of a dependency graph. The output is a self-contained HTML file viewable in any browser.
    AGPL 3.0
  • Export the context-window graph as an interactive HTML visualization. Nodes represent chat/session windows; edges show overlap, supersession, temporal order, or shared scope.
    Apache 2.0
  • Add a repository to the code graph to enable tool discovery and match natural language goals to the right tools.
    MIT
  • Plot mathematical functions with optional derivative visualization and critical points. Customize graph style, range, and output format.
    MIT