"Using AI Techniques with MCP for Project Assistance" matching MCP servers:

Enables secure execution of Python code, SQL queries, and metric fetching through MCP with ephemeral Docker sandboxing.

A focused project memory system that provides knowledge graph capabilities and SQLite database operations for intelligent entity tracking and workflow management. It enables AI models to maintain persistent project context through 17 specialized tools, 10 resources, and 27 pre-built prompts.

Enables integration with financial transaction data through REST APIs, PostgreSQL databases, and document storage systems. Demonstrates agentic AI capabilities by connecting to Alpha Vantage API and managing financial data through natural language interactions.

Enables task management (create, list, update tasks with priority and status) using SQLite storage via MCP tools.

Enables task management through natural language: create tasks, list and filter them, and update their status. It uses SQLite for persistence and supports both local stdio and remote SSE transports.

The Materials Project MCP Server is server that provides programmatic access to the Materials Project database. It enables LLMs, to search, analyze, and retrieve up to date materials science data.

MCP server that connects AI assistants to Redash, enabling listing of assets, read-only query execution, dashboard inspection, and alert management through the Redash API.

A safety-gated Python MCP server for Metabase that lets MCP clients and agents inspect Metabase, run governed queries, and create or maintain dashboards, cards/questions, collections, snippets, permissions, and other Metabase assets through the Metabase REST API.

A collection of MCP servers for database management and Gmail integration, allowing AI agents to perform database queries and email operations.

Enables AI agents to safely interact with Supabase through read-only and gated-write tools, with bounded queries, allowlists, and explicit project targeting.

Enables project and task management through a lightweight SQLite database, allowing users to create projects, add categorized tasks, track status changes, and get project statistics through natural language commands.

Enables exploring Microsoft Fabric / Power BI workspaces and semantic models, and executing ad-hoc DAX queries.

Enables AI tools to query context from a local JSON data source via stdio, demonstrating the Model Context Protocol.

MCP server that allows Claude AI to interact directly with MySQL databases, enabling query execution and table information retrieval through natural language.

A Model Context Protocol (MCP) server for developing Django applications. It exposes Django project information through MCP tools, enabling AI assistants to better understand and interact with Django codebases.

Enables chat, document search (RAG), and a declarative SQL tool builder over MCP so any client can use these capabilities.

MCP server offering tools to add numbers and fetch GitHub repos, a resource for apartment rules, and a prompt to explain SQL queries.

Enables AI agents to interactively interrogate database schema metadata using SchemaCrawler.

A server that enables document searching using Vertex AI with Gemini grounding, improving search results by grounding responses in private data stored in Vertex AI Datastore.

This read-only MCP Server allows you to connect to Microsoft Project data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).