"A tool for finding academic papers using semantic search and citation analysis" matching MCP servers:

Provides semantic code search over codebases using local embeddings with natural language queries. Supports hybrid search, file watching, and respects .gitignore.

Indexes codebases using semantic embeddings for natural language search, enabling developers to find code with queries like 'how does authentication work'.

Enables AI coding agents to perform semantic code search locally, finding code by meaning rather than exact keywords.

Enables semantic code search over local repositories, providing tools like semantic_search and list_indexed_repos to Claude Code, so users can find relevant code sections via natural language instead of grep.

Enables AI agents to perform semantic search over codebases by converting natural language queries into efficient search patterns like grep and ripgrep. It utilizes LLMs to verify relevance and find code snippets that traditional keyword-based searches might miss.

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.

AutomateLab Citation Intelligence reports which URLs ChatGPT, Claude, Perplexity, Gemini, Bing and Google AI Overviews cite. Self-hosted with your own engine API keys. Product and documentation: https://automatelab.tech/products/mcp/citation-intelligence/

Provides AI coding agents with structured access to indexed codebases via semantic search, symbol analysis, and file reading tools.

A stdio MCP server that enables an agent to vet its own draft before answering, returning per-citation verdicts for fabricated, retracted, or mismatched references along with a fix list, and flagging numbers in the text that do not appear in supplied source strings or files.

Enables LLMs to perform addition calculations through a stdio-based MCP server with an add_numbers tool and type-safe validation.

Semantic navigator for MCP tools that finds relevant tools by natural language intent, reducing token usage by 95%.

Enables users to preprocess, analyze, and visualize CSV data through comprehensive tools for data manipulation, statistical analysis, and graph generation.

A Model Context Protocol server that provides a scratchpad tool for LLMs to organize thoughts, take notes, and plan approaches to complex problems.

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.

MCP router that fronts your other MCP servers behind a few small generic tools, so their tool definitions stay out of the context window and are discovered on demand.

Exposes a governed semantic layer to AI agents so they select metrics and dimensions from a closed, engineer-declared vocabulary instead of writing SQL. Validates every typed call against the contract, rejects out-of-contract requests with structured errors and suggestions, and returns query rows together with the compiled SQL and dbt lineage for auditing.

A tool discovery MCP server that integrates with Azure DevOps wikis and code-graph-rag to match natural language goals to tools, enabling tool composition and proxy testing.

Encoding-aware, indentation-smart file tools for AI coding agents. 20+ tools including read/edit with automatic encoding detection, smart indentation conversion, SSH, SFTP, process management, and system utilities.

Provides natural language search capabilities for Spryker GitHub repositories, packages, and public documentation. It enables code-level searches across Spryker organizations to help developers find relevant modules and technical information.

Enables AI-assisted analysis and optimization of Cloudflare D1 databases through comprehensive schema introspection, relationship mapping, validation, and optimization recommendations. Demonstrates semantic intent patterns with hexagonal architecture for maintainable database development workflows.

Enables AI agents to safely describe, query, and compute metrics across SQL databases using open-format semantic models, custom context, and skills, with read-only and dialect-checked execution.

An MCP server that enables natural language search capabilities for Spryker packages and code across GitHub repositories, allowing users to find Spryker modules and documentation using conversational queries.

A server built on mcp-framework that enables integration with Claude Desktop through the Model Context Protocol.

Provides a semantic intelligence layer for SQL Server databases, enabling AI agents to understand schema structure, relationships, and safely interact through policy-gated tools.

Provides structured semantic context for JavaScript/TypeScript codebases, enabling coding agents to navigate, review, and change code with explicit uncertainty.

A standalone MCP gateway/proxy server that lets any MCP-compatible client search and call tools across multiple downstream MCP servers through a single mcp proxy tool.

MCP server for alive-analysis. Query, search, and retrieve structured analysis history written with the ALIVE loop (Ask→Look→Investigate→Voice→Evolve), plus dashboard JSON export.

An MCP server over stdio that lets agents find code by meaning using local Ollama embeddings and trace callers or callees through real tree-sitter AST parsing rather than regex or keyword matching. It shares the same search and trace engine as the companion CLI, so MCP-native agents and shell-only agents get identical, reproducible results.

Provides a 'reflect' tool that creates cognitive checkpoints for AI assistants, forcing structured step-by-step reasoning through complex problems to improve accuracy and maintain context during task execution.

MCP server for persistent project knowledge management, enabling AI assistants to store, search, and reuse project analysis insights with freshness checking and impact analysis.