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"Using a search engine to find evidence to answer a question" matching MCP servers:

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    Enables automated migration of Vue projects to React with intelligent analysis, task management, and learning from user modifications.
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    MIT
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    A code understanding and generation system designed for Galacean Engine that helps LLMs comprehend the engine architecture and generate high-quality engine code based on user intent.
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    Eyes for AI coding agents: deterministic MCP server that tells the LLM which CSS rule wins, in which file, on which line — and why. Cascade verdicts, blast radius, interaction timelines, pixel-perfect audits.
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    Apache 2.0
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    Audits AI agent skills for safety using static, semantic, adversarial, and supply-chain analysis, providing scores and risk flags. Can be run via CLI, CI, or as an MCP tool from Claude Code, Cursor, and Codex.
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    Apache 2.0
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    A task-aware context compression layer for Agent workflows, RAG pipelines, and AI Coding assistants, reducing noisy logs, retrieval chunks, and code context into high-signal LLM inputs via CLI, Python SDK, and MCP.
    363
    MIT
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    A local code-intelligence engine for AI agents that indexes repositories into a PostgreSQL-backed code graph and serves structured, token-budgeted context over MCP and HTTP, enabling targeted queries on symbols, dependencies, contracts, and impact analysis.
    Apache 2.0
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    Enables AI agents to perform semantic code search across entire codebases using natural language queries. Provides fast indexing and ranked search results with line numbers and file paths through the Seroost search engine.
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    A local-first, agent-agnostic MCP server that provides semantic search, persistent memory, and automated code review capabilities for development workflows. It leverages the Auggie SDK to offer advanced tools for codebase indexing, implementation planning, and deterministic static analysis.
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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.
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    MIT
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    Enables semantic code search across indexed code folders using vector embeddings, with support for multiple embedding providers and automatic file watching. Provides an admin UI and integrates with MCP clients for natural language code queries.
    MIT
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    Semantic + lexical code search as an MCP server. Agents query in natural language and get back ranked file:line ranges to read precisely.
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    MIT
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    Provides safe, read-only access to memory analysis and debugging functionality through the Model Context Protocol, allowing users to examine computer memory for software development, security research, and educational purposes.
    62
    MIT