"A project management and issue tracking tool" matching MCP servers:

MCP server for creating, listing, inspecting, and validating tracking plans for ecommerce and lead-generation businesses, with JSON storage and TypeScript implementation.

Enables AI agents to discover official public data sources, inspect their metadata and endpoint parameters, and execute live queries through a unified response envelope with a 500 ms budget.

Enables AI agents to index and search across SQLite databases and CSV files to discover table schemas and column metadata. It provides a unified MCP API for data source management and structural exploration through natural language.

基于Model Context Protocol (MCP) 的A股实时行情查询服务器，支持查询A股实时价格、历史K线数据、财务信息及市场概况。

Enables AI agents to interact with the WYGIWYH expense tracking API through 75 dynamically generated MCP tools. Supports comprehensive financial operations including transaction management, account handling, recurring expenses, and investment tracking.

Enables programmatic management of a Dify instance, including datasets, apps, and tools.

Enables deterministic aggregation, BM25 keyword search, and report generation over a large IT ticket-history dataset through MCP tools, prompts, and client-model sampling.

Read-only MCP tools for TROCCO API, enabling workflow and BigQuery datamart audit information retrieval.

Enables collecting data from configurable sources such as Jira, SonarQube, Uptime Robot, npm audit, and HTTP endpoints, then exporting it to an Excel file with one sheet per source.

Provides cryptocurrency market data using the CoinGecko API

This server facilitates scalable discovery and execution of OpenAPI endpoints using semantic search and high-performance processing, overcoming limitations of large spec handling for streamlined API interactions.

A Node.js-based MCP server that extracts numbers from text and generates statistical chart data such as bar, pie, and line charts based on frequency. It enables AI agents to perform data extraction and visualization tasks through the Model Context Protocol.

Exposes a synthetic issue tracker and pipeline warehouse as callable tools so an agent can answer operational questions about tickets, pipeline health, runs, incidents, and governed metrics with every claim cited to the exact tool call it came from. All writes are proposal-only, requiring human approval through a gated apply path that logs each step for audit.

Provides stock market data and trading capabilities using the yfinance library

Enables AI assistants to interact with Eclipse Dataspace Components (EDC) connectors for dataspace operations including asset, policy, contract, catalog, negotiation, and data transfer management.

Give your AI agent the entire China A-share market: 55 datasets of prices, financials, capital flows, corporate events and futures/options, stored locally and queryable with read-only SQL. Built point-in-time with delisted stocks kept, so backtests don't lie — no account, no API key.

Enables users to convert a vendor partner directory (such as PartnerPage or the Shopify Partner Directory) or a trade body member list into one company row per listing, each carrying website, domain, tier, tags, and location for Clay-ready output. It runs the extraction on Apify, returning dataset rows for up to 20 directory URLs with optional deduping, detail enrichment, and a cost cap.

Enables an AI assistant to answer customer-success questions by synthesizing simulated billing, support ticket, and product usage data into composite churn-risk scores, bands, and plain-language explanations for fictional accounts. It exposes raw-data tools, a synthesis tool, and a methodology resource so users can list at-risk accounts or get a per-account health summary.

Enables querying and mutating data across multiple sources (CSV, Google Sheets, SQLite, PostgreSQL, MySQL, MongoDB, Oracle) through a dynamic GraphQL API, with flexible filtering, batching, persisted queries, and dynamic source switching.

Minimalistic MCP server that lets AI assistants inspect, quality-check, and clean CSV datasets through tools, resources, and prompts, without needing local file access.

A server that provides tools to scrape websites and extract structured data from them using Firecrawl's APIs, supporting both basic website scraping in multiple formats and custom schema-based data extraction.

Enables agent tools to validate queries, assess token costs, and extract structured datasets from unstructured text using multiple LLM providers.

Provides real-time and historical cryptocurrency market data from multiple exchanges (Binance, Kraken, Coinbase Pro) with Redis caching and rate limiting support.

Exposes local DuckDB pizza sales data as MCP tools for querying store-level and total sales metrics via natural language, enabling local LLMs to perform real-time analytical queries.

Enables AI to interact with Microsoft Access (.mdb, .accdb) and SQLite 3 databases, including read-only support for Access 97 databases. Supports executing SQL queries, importing/export data from CSV and Excel files, and storing notes about database files.

Provides stock market data and computes technical indicators like EMA, MACD, and RSI across multiple timeframes using the LongPort API and TA-Lib. It enables users to perform detailed financial analysis and multi-timeframe market reviews through standard MCP tools.

Enables schema-aware exploration of JSON data by uploading samples, flattening nested structures, and using heuristic search with token overlap and fuzzy matching to find field paths for target names, accelerating ETL and API onboarding workflows.

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

A stdio MCP server exposing a validate_emails tool that lets agents screen email lists without sending mail or probing SMTP, checking syntax, DNS/MX records, disposable domains, role accounts, free providers, typo suggestions, and SPF/DMARC. Each address comes back with a valid/risky/invalid/unknown verdict plus machine-readable reason codes so agents can clean leads and signups before outreach or import.

Enables AI assistants to interact with DBT (Data Build Tool) projects, allowing them to query project metadata, inspect models and sources, view compiled SQL, and run DBT commands.