MCPInstall
Directory

MCP servers

394 servers that let your AI assistant read data and take actions in the tools you use.

394 results“retrieval”

mcp-agents

kishan0725

Reference implementations of Model Context Protocol (MCP) agents for file system operations and weather data retrieval

File SystemData+4

Model Context Protocol (MCP) for the Python dataretrieval package

DataText+1

sprite-codia-mcp

duyquangnvx

SpriteCodia is a tool that leverages the Model Context Protocol (MCP) TypeScript SDK to efficiently crawl and extract sprites from Codia within Figma, simplifying asset retrieval for developers and designers.

TextDesign+3

The demo MCP server facilitates data retrieval from a database and integrates with the Anthropic LLM provider. It supports easy deployment via Docker, making it simple to build and run. Key features include efficient data handling and seamless server initialization.

DatabaseData+5

mcp-server

dennismartis

The mcp-server is a basic Model Context Protocol server that offers a simple note storage system. It features a custom URI scheme for notes, allows users to add notes, and provides a summarization tool with customizable detail levels. Ideal for efficient note management and retrieval.

NoteStorage+8

The mcp-backlog-server-cursor is a lightweight server designed for managing and processing data in a streaming context. It supports efficient data retrieval and offers easy integration with various environments, making it ideal for real-time applications.

DataIntegration+10

mcp-simple-server-cursor is a lightweight MCP server designed for easy setup and integration. It supports cursor-based data retrieval, making it efficient for paginated data access. Ideal for developers looking for a straightforward solution to implement MPC features in their applications.

DataIntegration+6

mcp-server

YunosukeYoshino

The mcp-server leverages the Model Context Protocol to provide robust tool servers utilizing Brave Search, ChatWork, and Discord APIs. Key features include deep search capabilities, ChatWork room management, and Discord message retrieval, offering users comprehensive data analysis and communication tools.

APISearch+11

mcp-servers

kuvanov-2

The MCP server for JIRA and GitHub integrates these platforms with VSCode, allowing seamless issue retrieval and search. It uses 1Password CLI for secret management, enhancing security and ease of use. Key features include JIRA issue fetching and GitHub file content access.

CLISearch+8

The discogsmcpserver provides a robust Model Context Protocol interface for accessing and managing music metadata. It features efficient data retrieval, enhanced accessibility, and supports various music-related queries, making it an essential tool for developers and music enthusiasts alike.

DataMusic+5

docscovery

the-dusky

An MCP server for documentation discovery and retrieval

Document

The mcp-servers-crawler is a tool for scraping MCP server information from GitHub. It automates the collection of project details, supports time filtering, and uses OpenAI's GPT-4o-mini for semantic analysis. Results are saved in JSON format, allowing for extensive data management and easy retrieval.

APIData+13

"Model Context Protocol (MCP) server, providing OCR processing for academic literature, intelligent retrieval, and RAG functionality."

ProcessingText+2

This project provides an MCP (Multi-Channel Pipeline) server that acts as a wrapper for the MLB Stats API. It allows you to easily access and process various MLB data points, including schedules, game results, and team information. This server is designed for efficient data retrieval and processing within an MCP framework.

APIData+11

MCP server for integrating with HubSpot CRM, allowing seamless creation, retrieval, and management of summary records as Note engagements, all linked to a dedicated shared contact record.

NoteCRM+6

RAGMCP

marlon19991

Proyecto de RAG (Retrieval Augmented Generation) MCP

CodeRAG

JonnoC

MCP Server for Neo4J-based GraphRAG (Graph Retrieval-Augmented Generation) for code projects

ProjectGraph

MCP server for 23andMe genetic data retrieval by RSID

Data

CaseCanopy

Denyme24

A comprehensive legal AI system that combines Retrieval Augmented Generation (RAG) for legal precedent search with automated document generation. Features include Supreme Court case law search, AI-powered legal document creation (PIL, RTI, Complaint), and seamless integration with Claude Desktop via Model Context Protocol (MCP).

SearchDocument+5

AI MCP Tool for Memory Enhancement Based on the characteristics of memory storage and retrieval in the book "Learning Methods," we have developed an AI MCP (Memory Conceptualization and Processing) tool to assist in memorizing key concepts. Features - Memory Entry Creation: Users can create memory entries by providing concepts that need to be memorized to the AI. - Question Generation: The AI will generate questions that prompt the recall of these concepts. - Database Storage: Both the concepts and the generated questions will be stored in a database. - Scheduled Retrieval: The AI will retrieve questions from the database according to a specific time schedule. - Cognitive Stimulation: By using a questioning approach, the tool stimulates the brain to recall the desired concepts, enhancing the brain's ability to store and retrieve memories.

DatabaseData+15

MCP server for Telegram bots, enabling message sending, forwarding, and channel info retrieval.

MessageEnd

GROWI MCP Server integrates with GROWI, offering page listing and retrieval features.

OffRate

RHAIS_UI

solaius

Red Hat AI Studio - Agent Building, Model Evaluation, MCP Servers, Safety Guardrails, Prompt Engineering, Retrieval Augmented Generation, Document Ingestion

DocumentModel

AI MCP Tool for Memory Enhancement Based on the characteristics of memory storage and retrieval in the book "Learning Methods," we have developed an AI MCP (Memory Conceptualization and Processing) tool to assist in memorizing key concepts. Features - Memory Entry Creation: Users can create memory entries by providing concepts they wish to remember to the AI. - Question Generation: The AI will generate questions that prompt the recall of these concepts. - Database Storage: Both the concepts and the generated questions will be stored in a database. - Scheduled Retrieval: The AI will retrieve questions from the database according to a specific time schedule. - Cognitive Stimulation: By asking questions, the tool stimulates the brain to recall the concepts, thereby enhancing the brain's ability to store and retrieve memories.

DatabaseData+15