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Showing 22 open source projects for "search"
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MCP Everything Search
An MCP server that provides fast file searching capabilities
Everything Search MCP Server is an MCP server that provides fast file searching capabilities across Windows, macOS, and Linux. On Windows, it utilizes the Everything SDK; on macOS, it leverages the built-in mdfind command; and on Linux, it uses the locate or plocate command. -
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MCP Server Qdrant
An official Qdrant Model Context Protocol (MCP) server implementation
The Qdrant MCP Server is an official Model Context Protocol server that integrates with the Qdrant vector search engine. It acts as a semantic memory layer, allowing for the storage and retrieval of vector-based data, enhancing the capabilities of AI applications requiring semantic search functionalities. -
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All-in-One Model Context Protocol
All-in-one MCP server with AI search, RAG
The All-in-One Model Context Protocol Server is a comprehensive MCP server implementation integrating services like GitLab, Jira, Confluence, YouTube, and more. It provides AI-powered search capabilities and utility tools to enhance development workflows. -
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VikingDB MCP Server
A mcp server for vikingdb store and search
An MCP server that interfaces with VikingDB, a high-performance vector database developed by ByteDance, enabling efficient vector storage and search capabilities. -
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xiaohongshu-mcp
MCP for xiaohongshu.com
...The project centers on authenticated actions and data access that matter to content operations, such as checking login state, publishing or scheduling content, fetching recommendations and search results, reading post details, and acting on comments. It’s packaged so MCP-capable clients (e.g., Claude Desktop, Cursor) can discover its tools via schemas instead of prompt guesswork, which improves reliability and reduces brittle automation. The repo highlights a growing community and provides links to a hosted landing page, signaling that the server is intended for practical use beyond a proof of concept. ... -
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Search1API MCP
A Model Context Protocol (MCP) server
The Search1API MCP Server is a Model Context Protocol server that provides search and crawl functionality using Search1API. It enables web and news searches, content extraction, and sitemap retrieval, integrating seamlessly with MCP clients. -
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Firecrawl MCP Server
Adds powerful web scraping and search to Cursor and Claude
firecrawl-mcp-server is the official MCP integration for Firecrawl that brings high-recall web scraping, crawling, and search into IDEs and agent runtimes. It exposes tools for single-page scrape, multi-URL batch jobs, site discovery, and search enrichment, returning cleaned, structured content suitable for downstream LLM reasoning. The server is designed to run with Firecrawl’s hosted API or self-hosted deployments, making it flexible for enterprise data-governance requirements. ... -
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MCP ZoomEye
A Model Context Protocol server that provides network asset info
The ZoomEye MCP Server is a Model Context Protocol server that provides network asset information based on query conditions, allowing Large Language Models to obtain data by querying ZoomEye using dorks and other search parameters. -
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MCP Kibela
MCP server implementation that enables AI assistants
The MCP-Kibela server is a Model Context Protocol server implementation that enables AI assistants to search and reference content stored in Kibela. This integration allows AI models to securely access information within Kibela, enhancing their contextual understanding and response generation. -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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MCP WebResearch
MCP web research server (give Claude real-time info from the web)
The MCP Web Research Server is a Model Context Protocol server designed to bring real-time web information into AI applications like Claude, facilitating efficient research on any topic. -
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Box MCP Server
A Box model context protocol server to search, read and access files
Box MCP Server is a Model Context Protocol (MCP) server designed to facilitate searching, reading, and accessing files stored on the Box cloud storage platform. It enables seamless integration with Box, allowing for efficient file management and retrieval through MCP-compatible clients. -
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Fli
Google Flights MCP and Python Library
...This approach enables faster, more reliable, and more stable access to flight information, avoiding the fragility associated with HTML parsing and UI changes. The library supports a wide range of flight search capabilities, including filtering by airline, departure time, number of stops, cabin class, and sorting by price or duration, making it suitable for both casual queries and advanced travel analysis. In addition to its CLI interface, fli includes a Model Context Protocol (MCP) server that allows AI assistants to interact with flight data using structured tools, enabling natural language queries and automation workflows. -
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ArXiv MCP Server
A Model Context Protocol server for searching and analyzing arXiv
arxiv-mcp-server bridges AI assistants and the arXiv repository through a clean MCP interface, enabling search, metadata retrieval, and content access without bespoke scraping. With simple tools like “search” and “fetch,” an agent can find papers, pull abstracts, and download PDFs for downstream summarization or analysis. The project includes packaging and CI to publish to PyPI, plus tests and linting for reliability. Issue threads show feature requests such as extracting embedded LaTeX and improving markdown conversion, reflecting active community use in research flows. ... -
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MCP Filesystem Server
Go server implementing Model Context Protocol (MCP) for filesystem
Filesystem MCP Server is a Go-based server implementing the Model Context Protocol (MCP) for filesystem operations. It allows for various file and directory manipulations, including reading, writing, moving, and searching files, as well as retrieving file metadata. -
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The Web MCP
A powerful Model Context Protocol (MCP) server
Bright Data’s Web MCP server gives AI assistants robust, real-time web capabilities through an MCP interface designed to avoid blocks, rate limits, and CAPTCHAs. It presents search, crawl, navigate, and extraction tools that agents can call directly, replacing brittle scraping prompts with typed operations. The README markets it as a “gateway” to the live web so assistants don’t fall back to stale training data. Bright Data also advertises a getting-started tier with a free monthly allotment, plus options for remote or self-hosted operation depending on governance needs. ... -
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MCP Server Giphy
An implementation of Giphy integration with Model Context Protocol
The MCP Server Giphy is a Model Context Protocol (MCP) server that enables AI models to search, retrieve, and utilize GIFs from the Giphy platform. It facilitates seamless integration of Giphy's vast GIF library into AI applications, enhancing their expressive capabilities. -
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Deep Research
Use any LLMs (Large Language Models) for Deep Research
Deep Research is a local-first research agent that orchestrates multiple LLMs to generate in-depth reports in minutes. It combines “thinking” and “task” model roles with live internet access to plan, search, read, and synthesize findings into structured outputs. The project emphasizes privacy: processing and storage happen locally, avoiding server-side retention of your queries and notes. A simple web UI lets you enter topics and configure models, while the backend streams progress as sources are fetched and arguments are weighed. It offers MCP server support and SSE APIs, so IDEs and agent clients can drive the same workflow programmatically. ... -
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Elasticsearch MCP Server
A Model Context Protocol (MCP) server implementation
This MCP server implementation provides interaction capabilities with Elasticsearch and OpenSearch, enabling functionalities such as document searching, index analysis, and cluster management through a set of tools. -
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GitHub MCP Server
GitHub's official MCP Server
The GitHub MCP Server exposes GitHub as a Model Context Protocol server so AI assistants can safely act on repos, issues, pull requests, gists, and more through a consistent tool interface. It’s designed to run locally or remotely and then be attached to MCP-capable clients (for example, Copilot Chat) so an LLM can search code, open files, create branches, draft PRs, label or triage issues, and query metadata without hard-coding GitHub APIs. The server defines tools and resources with fine-grained scopes, leaning on GitHub’s auth to enforce least privilege and auditable access. It supports both stdio and HTTP transports, enabling IDE and headless integrations, and adopts common MCP behaviors like prompts, schemas, and tool definitions to keep agent calls predictable. ... -
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ENScan Go
ENScan_GO is an enterprise information reconnaissance tool
ENScan_GO is an enterprise information reconnaissance tool focused on Chinese corporate data sources. It aggregates official and third-party APIs to pull records like ICP filings, affiliated/holding companies, apps, mini-programs, and WeChat official accounts, then exports merged results for analysis. The tool targets analysts who need one-click collection and normalized output to reduce manual lookups across registries and platforms. Recent releases added a reworked task model with... -
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Serena
Agent toolkit providing semantic retrieval and editing capabilities
Serena is a coding-focused agent toolkit that turns an LLM into a practical software-engineering agent with semantic retrieval and editing over real repositories. It operates as an MCP server (and other integrations), exposing IDE-like tools so agents can locate symbols, reason about code structure, make targeted edits, and validate changes. The toolkit is LLM-agnostic and framework-agnostic, positioning itself as a drop-in capability for different chat UIs, orchestrators, or custom agent... -
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FlowLens MCP
Open-source MCP server that gives your coding agent
...It works together with a companion browser extension: when a user reproduces a bug or a complicated UI interaction, the extension captures a rich session log, including screen/video recording, network traffic, console logs, DOM events, storage changes, and more, and exports it. The MCP server then loads this captured “flow” and exposes it to the AI agent via the Model Context Protocol (MCP), letting the agent examine, search, filter, and reason about the session just as a human developer would, without needing the agent to re-run the flow or rely on minimal reproduction data (logs, screenshots).
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