"Using Strava Data for Analysis or Integration" matching MCP servers:

Integration project for Model Context Protocol (MCP) servers with Claude Desktop App, enabling filesystem operations, development support, and file management through natural language.

Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.

Enables AI agents to invoke a local Stata installation, including a Windows Stata build under Wine on Linux and macOS, for regression analysis, econometrics, paper replication, and empirical research with command guards, resource monitoring, and automatic log capture.

Enables Large Language Models to access and manipulate Autodesk Revit models through a pyRevit-based bridge and the Model Context Protocol.

Enables execution of Snowflake stored procedures through the MCP server by providing a framework to define, manage, and call procedures from specific schemas or individual procedures.

Local MCP server that registers restricted Python filters and runs them against local JSON, YAML, and TXT files, enabling safe data filtering and file conversion.

MCP server enabling AI agents to programmatically connect to and control Apache Superset instances, allowing users to manage dashboards, charts, databases, datasets, and run SQL queries through natural language interactions.

Enables integration of local LLM capabilities with MCP-compatible clients like Claude Desktop, Continue.dev, and Cline. Provides tools for processing text prompts through local language models using a customizable inference function.

A Model Context Protocol server that enables Claude to load CSV files and execute JavaScript data analysis scripts for advanced data exploration and insights generation.

A server that integrates trained Random Forest models with Bee Framework, enabling ReAct interactivity for AI tools and agents.

A simple MCP server implementation in TypeScript that communicates over stdio, allowing users to ask questions that end with 'yes or no' to trigger the MCP tool in Cursor.

Enables LLMs to safely execute pandas code for data analysis and generate interactive visualizations through MCP protocol.

Enable Claude (or any other LLM) to interactively debug your code (set breakpoints and evaluate expressions in stack frame). It's language-agnostic, assuming debugger console support and valid launch.json for debugging in VSCode.

A server that enables AI assistants to understand and interact with Unity projects in real-time, providing access to scene hierarchy, project settings, and the ability to execute code directly in the Unity Editor.

MCP-ORTools integrates Google's OR-Tools constraint programming solver with Large Language Models through the MCP, enabling AI models to: Submit and validate constraint models Set model parameters Solve constraint satisfaction and optimization problems Retrieve and analyze solution

This server implements the Model Context Protocol to provide sentiment analysis of text, returning polarity, subjectivity, and overall assessment (positive, negative, or neutral).

Provides filesystem access and integration with Z.ai's GLM-4 models for code generation and reasoning tasks. Designed to work as a git submodule with automatic parent repository detection.

MCP server that gives AI agents isolated, named Linux computers with stable IDs and lifecycle control. Supports multiple backends like Docker, Fly Machines, Modal, and E2B, with a dashboard for managing sandboxes.

Enables Claude Code to work with personal data that stays on the local machine, running SQL, Python, and file/schema inspection in a sandboxed compute-to-data setup that returns only aggregates, schemas, synthetic fixtures, and pseudonymized results. Raw records, file names, and protected values never reach the Anthropic API, so Auto mode can stay hands-off.

Enables a bot to inspect, query, create, edit, and script Roblox Studio instances in token-cheap batches, plus run Luau, playtests, screenshots, and inputs through Roblox's official Studio MCP connection. It runs locally over stdio or an authenticated local HTTP endpoint, returning small structured answers instead of dumping whole games into context.