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164,225 tools. Last updated 2026-05-31 04:16

"CodeQL static analysis tool and semantic code analysis platform" matching MCP tools:

  • List all gograph MCP tools and their purposes. Get recommended workflow sequences for static analysis of Go code.
    MIT
  • Detect existing feature flags in your codebase to prevent duplicates and encourage reuse. Uses file search, git history, semantic matching, and code context analysis.
    MIT
  • For static dependency analysis of Rego policies, identify all input/data leaves and rules a given reference transitively depends on.
    MIT
  • Resolve ABAP symbols from source code using semantic analysis to retrieve types, scopes, descriptions, and packages from the SAP system.
    MIT

Matching MCP Servers

  • F
    license
    A
    quality
    C
    maintenance
    The server facilitates natural language interactions for exploring and understanding codebases, providing insights into data models and system architecture using a cost-effective, simple setup with support for existing Claude Pro subscriptions.
    Last updated
    4
    24

Matching MCP Connectors

  • Execute Python code with automatic retry and intelligent error analysis. On failure, it diagnoses the error, searches past solutions, and suggests fixes for robust execution.
    MIT
  • Quickly validate Java syntax by providing a file path or inline code. Returns syntax errors without semantic analysis for rapid feedback.
    MIT
  • Create or update a markdown analysis document for source code with YAML frontmatter including source path and covered line ranges. Use to persist code analysis results and maintain a consistent registry.
    MIT
  • Compare static analysis with runtime data to identify stores missing from instrumentation or dynamically created during execution. Use after app runs to verify coverage.
    MIT
  • Analyze AI agent skills for security risks including prompt injection, malicious code, and credential handling using static analysis across 8 risk categories. Returns risk scores and detailed findings.
    MIT
  • Retrieve daily platform statistics including volume, fees, trader counts, and market activity from the Beefy P&L subgraph for trend analysis and historical performance.
    MIT
  • Extract function names from PureScript code snippets, focusing solely on functions while excluding data types and classes. Ideal for quick code analysis and understanding.
    MIT
  • Run static analysis in isolated environments to prevent local configuration drift. Validates Python, JavaScript, TypeScript, and Rust code using Ruff, ESLint, or Clippy for consistent results.
  • Uses CodeBERT deep learning to classify code as malicious or benign, detecting obfuscated payloads and novel attack patterns that static rules overlook.
    MIT
  • Analyzes semantic differences between two Git branches, detecting conflicts in code logic, signatures, exports, and cross-file dependencies that Git's textual merge overlooks. Returns a per-file report of all semantic changes and conflicts.
    MIT
  • Find analysis tools for your data or question. Uses semantic search across statistical and ML tools to match your dataset and query.
    MIT