"JobSpy job search tool or library" matching MCP servers:

An MCP server that retrieves resume/experience evidence relevant to a job description via vector RAG, and tracks fit-analysis results in a configurable tracking store (Notion or SQLite), with tools like match_job, push_to_tracker, and list_applications.

Enables dynamic tool discovery and loading for Claude using BM25, regex, and semantic search algorithms. It supports managing a catalog of over 10,000 tools with minimal context overhead and provides a REST API for tool management.

This MCP server enables AI agents to search and retrieve exact, cited passages from a large corpus of public-domain books, including full-text search, book metadata, chapters, quotes, and 'ask book' Q&A. Payments are handled via x402 micropayments on Base.

Provides a 'library keeper' sub-agent that ingests PDF/EPUB books and answers questions grounded in them via local embedding search, with deterministic classification and knowledge gap logging.

Provides a Google search tool via the Serper API, returning structured results and a summary answer for LLMs like Claude.

Enables a persistent local library for mathematical PDFs with cached LaTeX extraction, full-text search in English and Greek, and page/image retrieval over MCP.

Provides token-efficient semantic search and document retrieval by indexing PDFs, text, and markdown files into local notebooks using ChromaDB. It enables AI agents to query relevant passages from large documents through local embedding models like Hugging Face or Ollama.

Enables AI agents to prepare job-tailoring prompts, export tailored resumes to Google Docs, inspect job details, and retry pending evaluations through JSON-RPC 2.0 tools.

Helps users find suitable LinkedIn job opportunities by automatically scraping listings, analyzing compatibility with user profiles using AI, and sending custom match reports via email.

This MCP server enables job intelligence retrieval and ranking, providing tools to list jobs, fetch details, access corpus statistics, and score candidates against job descriptions using staged retrieval to optimize LLM context usage.

Enables semantic search across documentation stored in Gemini FileSearchStores, returning AI-generated answers with source citations.

An MCP proxy that embeds tool definitions and returns only the top-k semantically relevant tools per query, reducing context usage and routing calls to upstream MCP servers.

Universal search engine for AI agents. Discover products, services, and businesses across every category. 10 MCP tools, zero LLM calls, millisecond responses.

Federated, local-first search for AI agents: one query fans across transcripts, files, a knowledge graph, a vector store, the live web, and YouTube, fused by trust-weighted RRF into one ranked answer. Five modes (grep/lexical/semantic/hybrid/rerank), runs entirely on your machine over MCP.

CLI-first web and code search for agents, with MCP support for integration with IDEs like Cursor, VS Code, and Claude Code.

Graph-based tool retrieval for LLM agents. Builds a tool graph from OpenAPI/MCP specs and retrieves multi-step workflows via hybrid search (BM25 + graph traversal + embedding), recovering accuracy from 12% to 82% with 79% fewer tokens. Also works as an MCP Proxy to aggregate multiple servers behind 3 meta-tools.

Enables AI agents to search local Markdown documents using natural language, with automatic indexing and section-level retrieval.

MCP search and evidence tool for AI agents. Rewrites queries, zooms into source domains, and returns sourced answers with metrics.

A custom MCP tool that integrates Perplexity AI's API with Claude Desktop, allowing Claude to perform web-based research and provide answers with citations.

MCP server for hybrid documentation search (keyword + vector) and RAG chat, enabling natural language queries with cited answers from indexed repositories.