"Data science and deep learning papers" matching MCP servers:

MCP server for Bitbucket Data Center that enables PR creation, review comment management, and rebasing workflows through natural language commands.

Pay-per-call MCP server offering crypto market signals, web page extraction, and GitHub repo auditing, with automatic settlement in USDC via the x402 protocol.

A sample MCP server built with FastMCP that demonstrates basic tools and a Google OAuth integration for accessing Google APIs like Calendar.

MCP server for persistent code exploration and diff-aware review, exposing explore and review tools to map call paths, blast radius, and generate explainable risk-scored reports.

Provides MCP integration for Atlassian Data Center products including Jira, Confluence, and Bitbucket.

MCP servers for self-hosted Atlassian Data Center (Jira, Confluence, Bitbucket) enabling AI assistants to search, manage, and interact with issues, pages, and pull requests.

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.

A FastMCP-based server designed for the banking and fintech domains, providing tools for database queries, Git operations, and deployment management. It features a modular architecture with reusable prompt templates and integrated security practices for sensitive data handling.

A single-user MCP server that exposes your GitHub activity to Claude via three read-only tools: recent commits, open pull requests, and repository summaries. Deployed as a Vercel function using Streamable HTTP.

Enables searching GitHub users and repositories, fetching details, and performing stock market technical analysis via AlphaVantage.

A local Git intelligence MCP server that provides deep repository analytics including hotspots, temporal coupling, knowledge maps, churn analysis, and risk scoring for AI agents.

A local Git intelligence MCP server that provides deep repository analytics including hotspots, churn, knowledge maps, and risk scoring, all computed from commit history without data leaving your machine.

Provides deep git file-level forensics tools to analyze detailed file histories, changes, and patterns within git repositories, focusing on individual file analysis rather than repository-wide operations.

A runnable MCP server for learning GH-600 domain 2.0, providing four example tools (repo info, issues, summaries, safe file read) and a resource, using deterministic in-memory data.

Enables users to import scientific figures together with their code, review and publish them as immutable releases into one user-chosen local library, then search, preview and materialize an exact confirmed template into any project from Claude Science, Cursor, Codex or other stdio MCP hosts. It keeps the catalog on disk and never executes plotting code, so the host agent inspects files while the server hashes, versions, gates and publishes them.

DocuMCP is an intelligent Model Context Protocol (MCP) server that revolutionizes documentation deployment for open-source projects. It provides deep repository analysis, intelligent static site generator recommendations, and automated GitHub Pages deployment workflows.

Provides AI agents with a toolset to query model inventories, trace dependencies, and analyze the impact of changes across machine learning models and data pipelines.

The Nx MCP server provides LLMs with comprehensive insights into your monorepo: project dependencies, file relationships, executable tasks, ownership metadata, technology stacks, custom generators, and Nx documentation. This deep context enables LLMs to produce code perfectly aligned with your archi

Enables users to securely access and manage Bitbucket Data Center projects, repositories, pull requests, branches, commits, and build statuses through natural language, using per-user OAuth 2.0 authentication and granular read/write permissions.

Enables AI coding agents to checkpoint workspace state, branch parallel attempts, inspect diffs, and roll back to known-good states mid-task through MCP tools, with automatic safety checkpoints to prevent data loss.