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20 Best Web Search MCP Servers: compared and ranked, November 2026Ranked from 2,120 matching servers on stars, growth, downloads and maintenance. Updated .

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    Enables automated migration of Vue projects to React with intelligent analysis, task management, and learning from user modifications.
    14 npm
    6
    MIT
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    Enables MCP clients such as Claude Desktop or Cursor to inspect a coffee-shop sales database schema, validate SQL, and run guarded read-only queries. It supports natural-language questions by exposing tools for schema description, SQL checking, and safe query execution.
    MIT
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    Enables AI coding agents to extract Figma design data and convert it into Flutter widgets and screens. Supports theme setup, component analysis, asset exports, and provides Flutter implementation guidance from Figma designs.
    44 npm
    241
    MIT
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    Indexes codebases cut at function and class boundaries into Oracle AI Database 26ai, letting AI coding tools search code by name or meaning, trace callers, callees and change impact, read per-module wiki pages, and recall facts from earlier sessions. All of it is served over the Model Context Protocol with embeddings computed in-database, so no source code leaves the machine and no API key is required.
    9
    MIT
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    Knot is a semantic and structural codebase indexer designed for AI coding agents and developers navigating large projects. It combines vector search and graph traversal to find code by meaning, analyze impact via reverse dependencies, and explore file architectures.
    7
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    MIT
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    Provides access to Ant Design component library documentation and information for automated code generation. Enables searching components by category or keyword, retrieving component props, examples, API documentation, and available icons.
    6
    6 npm
    ISC
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    Enables AI coding assistants to semantically search codebases by meaning rather than exact text, with zero external daemons and fully local embeddings. Works out-of-the-box with Claude Code, Gemini CLI, Antigravity, and Cursor.
    4
    MIT
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    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.
    6
    MIT
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    Enables token-efficient structural code exploration using tree-sitter AST parsing, with tools for symbol search, outlines, source unfolding, call graphs, and related-file discovery.
    1
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    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.
    6
    26 npm
    200
    MIT
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    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.
    4
    MIT
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    An MCP server that scans codebases to extract structural information (classes, functions, etc.) with flexible filtering options and outputs in LLM-friendly formats.
    1
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    GPL 3.0
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    A local MCP server that provides semantic code search for Python codebases using tree-sitter for chunking and LanceDB for vector storage. It enables natural language queries to find relevant code snippets based on meaning rather than just text matching.
    3
    108 PyPI
    4
    MIT
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    Enables AI assistants to perform intelligent semantic code search across codebases using local AI embeddings for meaning-based retrieval.
    6
    26 npm
    MIT
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    Enables local detection of protected health information in source code before it reaches LLM prompts, log statements, or analytics calls.
    2
    62 npm
    MIT
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    Provides a memory server for coding agents over MCP, capturing and retrieving the meaning and rationale behind code decisions down to the function level. It enables agents to search product memory, get task context, and propose new memories to avoid re-deriving or re-breaking past decisions.
    9
    MIT
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    Enables coding agents to map a multi-repo workspace by resolving which repository a service name refers to, reading short per-repo cards, listing related repos with file-and-line evidence, finding where a table, package, path, or symbol lives across repositories, and refreshing the map. It answers orientation, localization, and cross-repo impact questions without the agent re-exploring every sibling repo.
    12
    37 PyPI
    4
    Apache 2.0
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    A local code-intelligence MCP server that provides structural, exact-query, related-search, and research capabilities from a validated repo-local index, enabling agents to perform deterministic lookups, semantic search, and code analysis.
    21
    MIT