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    Compose arbitrary MCP tools with JavaScript through one agent-agnostic stdio MCP server. It exposes an exec tool that enables dynamic tool discovery, schema inspection, and invocation with JavaScript code.
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    MIT
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    Renders source code as beautiful SVG or PNG images with syntax highlighting, line numbers, and diff support. Ideal for AI agents to present code visually to humans or for sharing snippets.
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    MIT
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    Wraps Claude Code as tools for MCP clients, enabling autonomous coding tasks via a 4-tool lifecycle with session management, async polling, and permission controls.
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    MIT
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    Search and resolve MCP server packages on the mpak registry, enabling agents to discover servers, inspect tools, and check credential requirements before installation.
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    MIT
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    A production-grade MCP server for the Code-Fundi API, enabling AI agents to map codebases, search semantically, and analyze blast radius. It provides tools for repository management, AI-powered research, and impact analysis before shipping changes.
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    MIT
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    Enables AI assistants to perform controlled Linux system administration tasks like reading logs, managing services, cron jobs, WordPress, and executing sandboxed Python code, with strict security constraints.
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    GPL 2.0
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    Exposes SQL Server and Snowflake schema metadata to AI coding agents, enabling schema search, join path discovery, and stored procedure metadata retrieval without live queries.
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    GPL 3.0
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    Search and explore a catalog of 2,000+ MCP servers — full-text search, trending, hot, categories, and side-by-side comparison — from any MCP client. A zero-dependency stdio bridge over the hosted awesome-mcp.tools endpoint.
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    MIT
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    Enables AI agents to interact seamlessly with Splunk environments through 20+ tools for search, analytics, data discovery, administration, and health monitoring. Features AI-powered troubleshooting workflows and supports multiple Splunk instances with production-ready security.
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    Apache 2.0
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    Knowledge graph for token-efficient code reviews. Builds a structural map of your codebase with Tree-sitter, tracks changes incrementally, and gives AI agents precise context via MCP tools. Features fixed multi-word search, qualified call resolution, dual-mode embedding (ONNX local + LiteLLM cloud), and output pagination.
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    Apache 2.0