"Common Lisp" matching MCP servers:

Elisp (Emacs Lisp) development support tools, running in Emacs

Static scanner for MCP/agent-gateway readiness anti-patterns, providing a 7-dimension R/Y/G score by scanning code and config for common failure modes.

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

Enables blazingly fast file and content searching in large codebases using ripgrep, with intelligent filtering, fuzzy finding, and directory tree visualization while respecting .gitignore and avoiding common bloat directories.

A local-first MCP server that indexes code repositories and enables AI assistants to search, fetch, and navigate code using BM25 hybrid retrieval, supporting common languages and tools like Codex and ChatGPT.

Enables coding assistants to check code for common health-data mistakes locally without an account, and, with a configured core service, de-identify clinical text, restore placeholders, and append tamper-evident audit log entries.

A Model Context Protocol server that provides tools to find regex pattern positions in files and list allowed directories, enabling text analysis with LSP-like functionality.

Lints local Markdown files or whole directory trees for broken relative links and images, empty link targets or text, heading hierarchy problems, and common README issues. Only relative targets on disk are checked, so external http(s) links are never fetched.

Provides code review and guideline loading based on Andrej Karpathy's coding principles, helping LLMs avoid common pitfalls like over-engineering and unnecessary changes.

An MCP server that exposes e18e module replacement data. It helps AI assistants suggest lighter, faster, or native alternatives to common JavaScript/Node.js packages.

Provides tools for managing tasks, searching docs, and running a heuristic quality gate to check agent output for common issues before human review.

Enables Claude to list directories, read text files, and search code within a designated read-only project folder, while skipping common dependency folders and blocking sensitive files.

Provides LLM clients with structured code intelligence through LSP servers, enabling queries for definitions, references, call hierarchies, and more.

Exposes Language Server Protocol (LSP) tools such as diagnostics, goto definition, find references, symbols, and rename as a stdio MCP server.

Enables agents to connect to Language Server Protocol servers as a headless editor, exposing LSP capabilities like diagnostics, rename, and formatting through MCP tools and resources.

Exposes type-aware code navigation and fast file search to AI agents via language servers, enabling definitions, references, symbols, and file lookup without reading entire codebases.

An MCP server that exposes Language Server Protocol features to external clients, allowing access to hover information, definitions, completions, references, and rename functionalities.

An MCP server that provides TypeScript 7 native language server capabilities (go to definition, find references, hover types, diagnostics) to coding agents, using the Go-based tsc compiler for fast and accurate semantic analysis.

An MCP server that exposes LSP-backed code navigation and editing tools to LLM agents using a single global config file to route file extensions to language servers.

Enables security scanning of code projects to identify common vulnerabilities like XSS, injections, SSRF, and path traversal issues. Provides local, offline scanning with severity-grouped results and actionable fix suggestions for improving code security.

MCP server that helps coding LLMs avoid re-solving common problems by serving verified minimal code samples and compatibility evidence, with tools to search, retrieve, and explain known solutions across languages and environments.

Enables AI coding agents to perform read-only semantic code navigation — definitions, references, diagnostics, hover, and document/workspace symbols — by bridging the Model Context Protocol to existing language servers. It also supports operator-approved, workspace-contained rename and edit previews with conflict checks and recovery.

Provides instant access to MCP development documentation, best practices, production checklists, common mistakes, architecture patterns, and testing strategies to help developers build production-ready MCP servers.

Provides MCP tools for common developer operations like file outlining, git commit context, test summary, process management, and waiting for conditions, returning structured JSON to reduce token usage.

Bridges the Model Context Protocol with Language Server Protocol to provide AI agents with persistent access to code intelligence features including navigation, diagnostics, refactoring, and completion across 7+ programming languages.

Provides any MCP-capable coding agent with shared, warm language-server intelligence and project-local configuration, so diagnostics, definitions, references, hover, symbols, code actions, formatting, rename, and sync behave consistently across harnesses and sessions. This lets users switch agent tools without reconfiguring LSP integrations or falling back to CLI verification.

Provides AI agents with language-aware code analysis through the Language Server Protocol, enabling tasks like getting code insights and diagnostics.

AI-powered static analysis for Unity projects, detecting common patterns, component relationships, and programming insights to augment developer workflows.

An MCP server that provides a semantic index and 14 bounded tools for AI agents to navigate Excel workbooks by symbols, references, and diagnostics, avoiding the need to read entire rows.

Enables coding agents to perform Java semantic navigation, diagnostics, compilation, JUnit testing, debugging, coverage, affected-test discovery, and safe refactoring previews without modifying source files.