"Finding LinkedIn users by educational background" matching MCP servers:

Vet ClawHub skills before installing them; detects prompt-injection, exfiltration, and other security issues, outputting a risk score with per-finding evidence.

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.

An MCP server that helps catch context drift in AI coding agents by comparing actual code changes against the original request, allowing users to keep or roll back unintended additions.

Enables agents to run semantic search across one or more local project directories by automatically maintaining a LAN-local Qdrant index with Ollama embeddings. Indexing, staleness checks, and incremental updates happen transparently, so users can query code by meaning without managing collections, chunks, or hashes.

Provides intelligent semantic code search using local AI embeddings, enabling natural language queries to find relevant code by meaning rather than exact keywords. Indexes codebases in the background with smart project detection and privacy-first local processing.

Provides educational tools for developers to learn programming concepts, review code, get best practices, compare approaches, generate learning paths, debug, explain code, and quiz themselves.

Enables AI coding assistants to perform local semantic code search using AST parsing and embeddings, finding code by meaning with exact file and line locations, plus AST-based usage lookup.

Indexes a workspace and exposes code-navigation tools to Codex, enabling symbol lookup, reference finding, dependency analysis, and security audit for local codebases.

Enables agents to validate Dockerfiles for build-breaking syntax errors, risky patterns like root users and secrets in ENV/ARG, and cache-order problems, returning every finding with its line and a fix. It also verifies referenced container images against public registries, reporting tag existence, digests to pin, supported platforms, last rebuild time, and end-of-life status with an upgrade tag.

Exposes boyter/scc code counting and complexity analysis to LLM agents via read-only tools like counting lines, finding top files, and cost estimation.

Provides code refactoring capabilities for TypeScript/JavaScript and Python through Language Server Protocol integration. Enables renaming symbols, extracting functions, finding references, and moving code between files via natural language commands.

A Model Context Protocol server that helps AI code editors locate TypeScript symbol definitions in codebases, particularly useful for finding original definitions of imported symbols and classes.

Provides LLMs with safe, read-only access to local codebases for searching, reading files, and finding function definitions. All source code remains local, ensuring privacy while enabling AI assistants to explore project structures and functionality.

Enables AI assistants to work with Chapel code, including compiling, linting, and accessing educational primers.

Enables AI-powered code analysis and repository scanning through six MCP tools, including house categorization, friction detection, recursive pattern finding, and equilibrium evaluation, with conversation memory and 24/7 cron operation on Cloudflare's free tier.

AST-aware TypeScript/JavaScript codebase exploration for AI agents, providing high-precision symbol resolution, reference finding, and structural analysis via MCP tools.

Provides unified development tools including code analysis, debugging, refactoring, documentation, testing, and project automation through multiple LLM providers (KIMI, GLM, OpenRouter). Features agentic audit capabilities with multi-model consensus for finding issues and generating direct fixes.

MCP server for local-first lexical code search, providing tools for searching code, finding symbols, and reading chunks from indexed repositories.

Enables AI coding agents to perform semantic code search locally, finding code by meaning rather than exact keywords.

Enables MCP clients to register projects and analyze source code through Tree-sitter WASM parsing, exposing tools for AST and symbol extraction, custom queries, reference finding, complexity and similarity analysis, dependency discovery, and text search. It also ships a web studio with a Monaco editor, AST explorer, Git view, and read-only SQLite console for interactive exploration.