"Secure Shell (SSH) Overview or Usage" matching MCP servers:

Enables developers and product owners to scan a codebase and extract a readable business overview—features, roles, access control, data model, and endpoints—along with findings on missing or inconsistent rules, and generate shareable HTML or Markdown reports and diagrams.

Verify-and-repair secure-coding harness that generates, hardens, audits, and scores Go code with a build and security scan feedback loop, and includes a transparent proxy to harden any client automatically.

Provides a secure, containerized Python sandbox for executing LLM-generated code with multi-layer isolation, along with JSON/CSV validation and workspace state snapshots.

Local MCP server that scans code for security issues (secrets, dependencies, configurations, risky patterns) and integrates with GitHub Copilot in VS Code for automated pre-commit reviews.

Enables AI-powered security scanning of codebases through conversational analysis, allowing users to assess, threat model, code review, DAST test, and generate security reports using natural language with Claude.

A Model Context Protocol (MCP) server for analyzing browser extension security, providing tools for vulnerability detection, signature checking, code review, and security evaluation.

MCP server that provides shell script linting via ShellCheck. Allows AI agents to analyze shell scripts for common errors, stylistic issues, and potential bugs.

A local MCP server that indexes a repository into line-range chunks and serves compact evidence packets to cut token usage when exploring or debugging code.

An AST-based MCP server that provides token-efficient codebase skeletons to LLM agents, reducing context token usage by 80-95% by exposing structural information instead of full source files.

Parses Unity text-serialized .prefab, .unity, and .asset files to output only Inspector-visible data in hierarchical YAML, reducing token usage by up to 96%.

Enables AI coding agents to reduce token usage by condensing source code into AST skeletons, extracting specific symbols, compressing logs, and estimating token budgets.

Analyzes JSX prop usage in React/TypeScript codebases using AST parsing, enabling prop usage tracking, component analysis, and TypeScript support.

Local code-graph engine for AI coding workflows: static analysis of Rust, Cangjie, ArkTS, TypeScript/JavaScript, C/C++, Python, and Shell projects into symbols, imports, call graphs, and quality gates, with pre-commit change review and impact analysis. Read-only by design — never executes build scripts or uploads code.

Cartograph is an MCP server that provides agent-native code intelligence by building a queryable code graph from a repository using tree-sitter and SQLite. It offers tools for symbol lookup, call graph traversal, blast radius analysis, and architecture overview to help coding agents answer structural questions about code.

Provides coding agents with a compact map of a TypeScript/TSX codebase, enabling direct answers about symbol locations, imports, dependencies, and references while reducing token usage.

A mcp server to allow LLMS gain context about shadcn ui component structure,usage and installation

Scans codebases for AI system usage and generates EU AI Act compliance reports.

Semantic code search MCP server that reduces token usage by ~95% by returning top relevant code chunks instead of full files.

A secure MCP server that exposes local repository context to ChatGPT/Codex with read-only access, path validation, and no generic shell.

Provides access to PrimeNG component documentation and generates code examples. Supports searching components, retrieving documentation, and creating practical usage examples for Angular UI development.