"Accessing Hevy workout tracking app data" matching MCP servers:

Enables AI agents to query structured data refined from unstructured web sources, including developer breaking changes, B2B pricing matrices, regulatory compliance, semantic search, and on-demand URL refinement.

Provides semantic search and knowledge base management for the micro-app micro-frontend framework by ingesting its source code and documentation.

Enables MCP clients to ask bilingual data questions, inspect database tables and schemas, and execute validated read-only SQL through exposed tools.

An MCP server that runs Apify scraping actors with quality-gated validation, scoring, and retries, returning embedding-ready chunks for AI agents.

A semantic layer query engine with MCP support, enabling AI assistants to query structured data through natural language and declarative interfaces.

Enables unified access to SQL, semantic vector search, and columnar analytics through a single MCP interface.

Enables Claude to answer plain-English questions by listing and describing database tables, running read-only SQL queries, and searching a folder of policy documents.

Multi-datasource MCP server that connects AI assistants to 6 database types (MySQL, PostgreSQL, ClickHouse, MongoDB, SQLite, Huawei DWS) with dynamic configuration, encrypted credential storage, and schema discovery.

Enables natural language querying of PostgreSQL via MCP, combining SQL, vector search, and knowledge graph with automatic routing and token-aware curation.

Enables querying and analyzing user, product, and order data with filtering capabilities and real-time statistics. Supports WebSocket connections to XiaoZhi AI platform with automatic reconnection.

Automatically routes natural language questions to RAG or Text2SQL paths to answer queries about virtual construction site data, supporting semantic search and structured aggregation.

Secure Edge Gateway for Data Normalization.

A production-ready Python MCP server supporting stdio and Streamable HTTP transports, providing tools for health check, user query normalization, knowledge base search, document retrieval, and RAG prompt construction.

Enables loading CSV text, filtering and aggregating datasets over Streamable HTTP, and optionally using Amazon Bedrock to turn query results into concise answers suitable for speech.

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Salesforce Data Cloud (beta): https://www.cdata.com/download/download.aspx?sku=LRZK-V&type=beta

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Google Data Catalog (beta): https://www.cdata.com/download/download.aspx?sku=HGZK-V&type=beta

A Model Context Protocol server implementation that integrates with KeywordsPeopleUse for accessing keyword research features including People Also Ask questions, Google Autocomplete suggestions, Reddit/Quora questions, and semantic keywords.

Enables AI applications to access and contextualize organizational knowledge sources including GitHub repositories and internal documentation through standardized MCP protocol integration. Features OAuth 2.1 authentication, vector-based semantic search, and optimized context chunking for enterprise development workflows.

Enables local data discovery by indexing metadata from SQLite, CSV, and Markdown sources, providing hybrid keyword and TF-IDF semantic search via MCP tools (listSources, indexSource, search, getSchema) and a REST API.

A Model Context Protocol server that bridges Microsoft Teams with MCP-compatible clients (LLMs, agentic frameworks, CLI), enabling chat integration, message search, and event streaming without traditional REST API endpoints.

A Model Context Protocol server that bridges Microsoft Teams and MCP-compatible clients, enabling chat integration, message handling, and advanced search capabilities without REST API endpoints.

A basic MCP server setup guide demonstrating how to configure and run Python-based MCP servers with integration examples for Bright Data web scraping and Apify Actors for product data collection.

Enables answering Formula 1 FAQ questions via vector search and web search using Bright Data.

Local-first personal wiki and memory server for AI agents. MCP clients can capture knowledge, retrieve context, read and maintain source-backed wiki pages, and carry project context between sessions.

Enables Claude Code to search, save, and relate local Markdown notes—lessons, do/don't rules, and task history—by project, ticket, epic, tags, or text, keeping everything on the user's own computer.

Enables LLM agents to query a contract data room using structured metadata filters and BM25 full-text search over contract articles, returning relevant contracts, justifying clauses, and explicitly excluded unknowns. It supports exhaustive list answers and citation-ready JSON for MCP clients.

Enables LLMs and AI agents to access real-time web data, search websites, and navigate the web without getting blocked. Includes 5,000 free monthly requests and supports web scraping, browser automation, and bypassing geo-restrictions.

Provides personalized Data Engineering learning updates by fetching recent news about DE concepts, patterns, and technologies, while tracking user knowledge to present only new information relevant to their learning journey.

AI for product teams. Connect all your company and customer knowledge to all of your other tools via BuildBetter's MCP.

Enables AI assistants to interact with a user's personal feed subscriptions, articles, highlights, notes, and tags through natural language, supporting tasks like search, summaries, tagging, and read-status management.

Access to many public datasets right from your LLM application.

Open-source agentic schema layer. Define metrics once in YAML, query governed data from any warehouse (Snowflake, BigQuery, Databricks, PostgreSQL, DuckDB) via MCP.

Search web using baidu with AI.

Enables SQL agents to connect to any SQLAlchemy-supported database via MCP, providing read-only SQL querying, automatic table summarization, and column content search.

Web search for AI agents. Up to 10 results for $0.001 USDC via x402 on Base. No API key.

A Model Context Protocol (MCP) server that enables LLMs to interact directly the documents that they have on-disk through agentic RAG and hybrid search in LanceDB. Ask LLMs questions about the dataset as a whole or about specific documents.

A persistent, trust-scored project memory for AI coding agents, backed by PostgreSQL + pgvector, providing durable memory of architecture decisions, bug patterns, and coding conventions.

Connects AI coding assistants to Google Cloud Discovery Engine APIs for semantic search, conversational RAG, and administration of datastores, documents, and configurations.

Exposes roughly forty tools over streamable HTTP so AI assistants can search an archive of sourced evidence, time series, forecasts, slides and datasets, reuse existing material with its citations, and write new sourced findings back. It also covers slide and deck management, feedback, photo and dataset access.

Enables natural language queries to be converted into policy-verified SQL, vector search, and knowledge graph plans, with evidence-backed answers and an audit log.