"A search for the GitHub repository OrionSmithers/agent-data-pro" matching MCP servers:

Enables AI models to access GitHub repository contents as context, with features to fetch entire repositories, specific file contents, and repository structures for use in AI interactions.

Anthropic's github MCP server, but better. Support for more endpoints. Including releases and tags, pull request reviews, statuses, rate limit, gists, projects, packages, and even pull request diffs. Indented to be used with MissionSquad's MCP API for secret management (aka your access token).

MCP Server for automated reverse engineering with IDA Pro.

A read-only remote MCP gateway that lets MCP-capable agents discover GitHub REST endpoints and run many read-only GitHub reads (files, issues, comments, pull requests, checks) inside a single sandboxed JavaScript execution, returning only the compact result needed. This cuts model/tool round trips and context use, with enforced read-only access, repository allowlisting, and GitHub App authentication.

Enables AI agents to directly manipulate Jupyter Notebook cells and structure through a secure, well-defined API, overcoming Cursor's AI agent mode limitations.

Drives a live ArcGIS Pro session from Claude via arcpy, enabling layer listing, dataset description, geoprocessing, and project inspection directly against an open project.

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

Enables local AI agents to manage GitHub Codespaces workspaces and execute remote tasks by checking out exact commits, running builds, tests, scripts or temporary services, downloading logs and artifacts, and stopping or exporting managed environments.

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

An extended PostgreSQL management and analysis server that provides database professionals with tools for schema management, query optimization, performance monitoring, and health analysis through a collection of specialized functions.

A local MCP server that enables AI clients to read ArcGIS Pro project information and execute ArcPy geoprocessing in the native ArcGIS Pro Python environment.

An MCP server that provides data bridging from Spring Boot interfaces and a lightweight Python sandbox for script execution. It enables agents to fetch data as Markdown or Parquet files and perform automated data analysis within a controlled environment.

Give your AI app any GitHub link and the job you want done. UGT gets the project running on your computer and hands you the result.

Enables coding agents to work on Windows through persistent PowerShell sessions, surgical file editing, code search, background job execution, and web research while avoiding context-heavy GUI automation.

Enables AI coding agents to work inside a live Unreal Editor for Fortnite session: write and compile Verse, place and wire Creative devices, edit Scene Graph entities, manipulate actors and assets, take screenshots, run playtests, and read editor logs via MCP.

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.

Enables code execution in isolated Docker containers with persistent IPython, Node.js, or R kernels, supporting file import/export and cross-session transfers via MCP tools.

An advanced MCP server that provides an agentic interface to Google's Gemini 3.1 models via Vertex AI, combining real-time Google Search, URL analysis, and Python code execution to solve complex multi-step research and data tasks.

Provides workspace-scoped file operations and command execution tools for building Cursor-style agents, along with system prompts and tool definitions for LLM integration.

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 coding agents to run Kubernetes inspection and Terraform plan/apply operations inside ephemeral gVisor-sandboxed jobs with short-lived, narrowly-scoped credentials, while routing destructive changes through a human approval gate.

A Python MCP server that allows programmatic interaction to find torrents programmatically on ThePirateBay, Nyaa and YggTorrent.

A multi-agent collaborative development bridge that enables TRAE Work to offload complex tasks to Codex executor, with tools for task submission, status tracking, artifact listing, and permission management.

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.

The Problem Modern distributed systems and AI agents require robust operational scaffolding. Simple CRUD apps or mock loops fail when subjected to real-world edge cases, asynchronous boundaries, and security constraints. The Solution An isolated execution platform for AI agents. An agent is given a broken service and a bounded toolset inside a disposable sandbox. Every command passes throug

Enables integration of Perplexity's AI API with LLMs, delivering advanced chat completion by utilizing specialized prompt templates for tasks like technical documentation, code review, and API documentation.

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.

Enables cost-effective repository analysis, code search, file editing, and task planning by wrapping the cursor-agent CLI through focused tools. Reduces token usage by offloading heavy thinking tasks from Claude to specialized operations with configurable output formats.

An orchestration platform for deploying parallel swarms of tool-enabled AI agents to perform complex tasks like code generation, system monitoring, and multi-perspective analysis. It features a unique chunked write pattern that enables the creation of large-scale documents and code files by assembling parallel agent outputs.

Enables external AI clients to invoke an autonomous coding agent that plans, fixes, and self-corrects code in an isolated Docker sandbox via run_task and run_tests tools.