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    Semantic React/TSX analysis MCP server that saves 70-90% tokens by using AST to retrieve precise component usages, prop flow, and state update information for AI coding assistants.
    10
    10 npm
    MIT
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    Enables AI agents to format SQL, explain queries in plain English, analyze schemas, build queries from natural language, and generate migrations, all without requiring a database connection.
    5
    29 npm
    MIT
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    Enables secure read-only querying of multiple database types (MySQL, PostgreSQL, MSSQL, Oracle) through natural language. Automatically reads database configuration from project files and blocks any data modification operations for safety.
    4
    10 npm
    1
    ISC
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    Analyzes SQL queries for performance issues, provides optimization suggestions with automated rewriting, and recommends indexes across multiple database dialects (PostgreSQL, MySQL, Oracle, SQL Server).
    1
    MIT
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    MCP server for comprehensive PyPI package intelligence, providing tools for dependency analysis, security scanning, health scoring, license compliance, and trend tracking.
    MIT
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    Enables AI coding agents to navigate and understand entire codebases through symbol-aware semantic retrieval and relational call graph traversal, supporting structural impact analysis and code modification workflows over MCP.
    Apache 2.0
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    Enables AI assistants to query and analyze Rell code via Language Server Protocol features like hover information, completions, diagnostics, and code actions. Automatically manages the Rell LSP server and provides resource-based access with real-time subscriptions.
    10
    7 npm
    MIT
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    Enables AI coding agents to preflight SQL, NoSQL, graph, warehouse, and vector queries against real schemas or pasted DDL, estimating cost/risk, suggesting verified rewrites, and explaining plans before execution. It supports 12 database engines and catches costly query patterns without running the query.
    9
    233 PyPI
    MIT
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    Enables AI coding agents to query a compiled typed symbol graph over MCP, revealing real callers, callees, blast radius, data flow, constraints, dead code, and commit-history signals before editing. Supports repo syncing and ranked context retrieval so agents can avoid structural regressions.
    27
    37 npm
    MIT
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    Enables efficient code navigation and retrieval through natural language search, BM25 ranking, and fuzzy matching across multiple programming languages. It drastically reduces token usage by allowing Claude to query specific code symbols and logic instead of reading entire files.
    13
    69 npm
    13
    MIT
  • F
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    Provides codebase indexing and retrieval tools that give AI agents token-efficient, query-relevant context packages (symbols, imports, and dependencies) instead of scanning entire repositories.
    6
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    Enables AI agents to perform read-only static analysis of Node.js backend projects, detecting database query anti-patterns, async bottlenecks, connection pooling mistakes, and dependency hygiene issues while returning structured evidence-backed findings.
    6
    MIT
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    Provides comprehensive development tools for FastMCP projects including documentation access, NPM package version management, and TypeScript type definitions retrieval. Enables developers to fetch FastMCP documentation, analyze NPM packages, and access MCP architecture information through natural language.
    6
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    Indexes Unreal Engine project C++ source, config files, dependencies, gameplay tags, replication, asset references, and log categories into a SQLite database and exposes tools for AI assistants to query structural and config info.
    17
    MIT
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    A local codebase retrieval tool that indexes a git repository into SQLite and provides query and retrieval capabilities over MCP stdio, enabling coding agents to search and retrieve code chunks from local repositories without external data transmission.
    4
    19 npm
    MIT