"Checking Supabase migrations in GitHub Actions" matching MCP servers:

Connects AI agents and MCP clients to Supabase Management operations through a single PipMCP API key, enabling project and organization discovery, hosted tool schema inspection, and policy-governed execution with approval-aware actions.

Enables Codex to rank available tools and skills, rerank code and documentation search results, and triage saved output artifacts using Jev-based relevance scoring while leaving final decisions to Codex.

An MCP relay that adds a use_jev tool to every connected server, letting the Jev model autonomously select and execute tool calls while the calling model supplies any required text values. It enables agents to delegate multi-step tool use across all configured MCP servers through a single unified interface.

Enables Codex to manage a local Claude Code companion through MCP, implementing a dual-agent workflow where Codex handles reasoning and review while Claude Code performs engineering tasks.

Enables Claude Code to control Firefox through tools for tabs, navigation, clicks, typing, scrolling, screenshots, page reading, forms, JavaScript, and console/network logs.

Enables MCP clients to read, summarize, create, update, and delete tasks on a team task board according to the caller's tenant and role. It also supports running the same board operations exposed to forms, JSON routes, Artisan, and the copilot.

Exposes 26 browser_* MCP tools that let an agent drive a local Chrome instance—opening and focusing tabs, reading pages, clicking, typing, uploading files, taking screenshots, recording GIFs, and inspecting console and network activity—even when the client runs inside Docker. Control is scoped to a dedicated tab group and protected by token authentication.

Enables users to describe an LLM fine-tuning workload once and receive ranked, task-aware GPU recommendations across a dozen cloud providers based on required VRAM/FLOPs, cost, and runtime. It surfaces the cheapest, fastest, and balanced options through MCP so coding assistants can plan training hardware without manual price comparison.

Enables AI agents to analyze employee GitHub activity including PRs, code reviews, comments, and contributions across repositories with time-range filtering for performance assessment and impact analysis.

Enables AI coding agents and human managers to coordinate work on GitHub Projects v2 through 20 tools and 169 actions for autonomous task checkout, heartbeats, reviews, token budgets, PRD generation, sprint planning, issue triage, and PRD-to-issues pipelines, backed by GitHub-native storage and MCP resources/prompts.

Turns GitHub Projects v2 into an agentic project-management layer where AI coding agents register, atomically claim and self-assign tasks, heartbeat, review each other's work products, and operate within token budgets. It also exposes 20 compound tools (169 actions) plus MCP resources, prompts, and sampling for AI-powered PRD generation, task breakdown, sprint planning, issue triage, and a PRD-to-issues pipeline, all stored natively in GitHub with no external infrastructure.

Enables AI coding agents and project managers to turn GitHub Projects v2 into an autonomous project management layer with task checkout, multi-agent swarms, PRD-to-issue pipelines, sprint planning, triage, and GitHub Actions/Releases/Branches support via 20 compound tools and 169 actions.

Enables AI agents and project managers to turn GitHub Projects v2 into an autonomous project management platform with task checkout, multi-agent coordination, PRD-to-issue pipelines, sprint planning, triage, and GitHub-native storage.

Enables AI coding agents and teams to turn GitHub Projects v2 into an autonomous task substrate for registering, claiming, tracking, reviewing, and completing work, while also supporting AI-powered PRD generation, sprint planning, issue triage, roadmap creation, GitHub Actions/releases/branches, and MCP resources/prompts.

Turns GitHub Projects v2 into an agentic task substrate where AI coding agents register, atomically claim and hand off tasks, heartbeat, submit work for review, and stay within token budgets. Also provides AI-powered PRD generation, task breakdown into issues and milestones, sprint planning, and issue triage — with all state stored natively in GitHub.

Enables AI coding agents to use GitHub Projects v2 as a shared task substrate, with registration, atomic task checkout, heartbeats, budgets, peer review, and self-healing coordination. It also automates PRD-to-issue pipelines, sprint planning, triage, roadmaps, GitHub Actions, releases, and branch workflows through MCP tools, resources, and prompts.

Turns GitHub Projects v2 into an agentic project-management substrate where AI coding agents register, atomically claim tasks, send heartbeats, review each other's work, and stay within token budgets, while also offering AI-powered PRD generation, task breakdown, sprint planning, and triage. Everything is stored in GitHub issues, project fields, and comments, so no external database or infrastructure is required.

Turns GitHub Projects v2 into an agentic task substrate where AI coding agents register, atomically claim and complete tasks, exchange heartbeats, review one another's work products, and operate within token budgets. Humans get AI-powered PRD generation, task breakdown, sprint planning, roadmap creation, and issue triage, with all state stored natively in GitHub issues, projects, and comments so no external infrastructure is needed.

Turns GitHub Projects v2 into an agentic project management layer where AI coding agents register, atomically claim and track tasks, heartbeat, review each other's work, and operate within token budgets, all backed by GitHub-native storage with no external infrastructure. It also gives humans AI-powered PRD generation, PRD-to-issues pipelines, sprint planning, triage, roadmap creation, and requirements traceability across 20 compound tools exposing 169 actions, plus MCP resources, prompts, and sampling support.

Enables AI coding agents and human project managers to turn GitHub Projects v2 into an autonomous management layer for task checkout, agent coordination, review workflows, token budgets, AI PRD generation, sprint planning, issue triage, and PRD-to-issues pipelines. All state is stored in GitHub issues, project fields, and comments, requiring no external infrastructure.

Enables AI coding agents and human managers to turn GitHub Projects v2 into an autonomous project-management layer with task checkout, multi-agent coordination, PRD-to-issues pipelines, sprint planning, triage, token budgets, and GitHub Actions/Releases/Branches through MCP tools, resources, and prompts.

Enables AI coding agents and human managers to turn GitHub Projects v2 into an autonomous task backbone, coordinating multi-agent work, generating PRDs, planning sprints, triaging issues, and shipping code through GitHub-native storage and 20 tools exposing 169 actions.

A Model Context Protocol server that enables LLM agents to manage GitHub repositories, issues, pull requests, branches, files, and releases through a standardized interface.

Enables AI coding agents to self-assign, coordinate, review, and ship work through GitHub Projects v2, with AI-powered PRD generation, sprint planning, issue triage, and token-budget enforcement.

Enables AI agents and human managers to orchestrate GitHub-based project work by self-assigning tasks, coordinating swarms, tracking token budgets, generating PRDs, planning sprints, triaging issues, and materializing tasks as GitHub issues, milestones, and project views.

Turns GitHub Projects v2 into an agentic project management layer where AI coding agents self-assign tasks, coordinate via heartbeats, submit work for review, and stay within token budgets. It also provides AI-powered PRD generation, sprint planning, issue triage, and a PRD-to-issues pipeline, all backed by GitHub-native storage with no external infrastructure.

Turns GitHub Projects v2 into an agentic project-management layer where AI coding agents can register, claim tasks, coordinate, submit work for review, and enforce token budgets, while humans can generate PRDs, plan sprints, triage issues, and create roadmaps using GitHub-native storage.

Enables local opencode agents to control a live Chrome browser via MCP tools, including tab management, JavaScript execution, clicking, form filling, page reading, screenshots, and console log retrieval.

Enables AI agents to register, claim tasks atomically, coordinate via heartbeats, and submit work for review while human managers generate PRDs, plan sprints, triage issues, and materialize tasks into GitHub issues using GitHub-native storage.

Turns GitHub Projects v2 into an agentic project-management platform where AI coding agents can register, claim and track tasks, coordinate via heartbeats, review work, and stay within token budgets. It also enables AI-powered PRD generation, sprint planning, issue triage, roadmap creation, and PRD-to-issue materialization using GitHub-native storage.

Enables AI coding agents to register, claim tasks atomically, coordinate via heartbeats, review each other's work, enforce token budgets, and ship code using GitHub Projects v2 as the backing store. It also gives humans AI-powered PRD generation, sprint planning, issue triage, and roadmap creation without external infrastructure.

Enables AI coding agents to use GitHub Projects v2 as an autonomous task backbone, with task checkout, atomic claims, heartbeats, peer review, token budgets, and PRD-to-issues automation. It also supports AI-powered sprint planning, issue triage, roadmap generation, and MCP resources/prompts.

Enables autonomous agents and MCP-compatible clients to enforce policy-approved actions using risk tiers, reversible checkpoints, and token approval bounds.

Enables AI coding agents to register, self-assign and coordinate tasks, track progress, review work, and manage GitHub Projects v2 with AI-powered PRD generation, sprint planning, issue triage, and PRD-to-issues pipelines backed entirely by GitHub-native storage.

Enables AI agents and MCP clients to discover and execute hosted project-management tools through one PipMCP API key, including reading work items and applying explicitly approved changes under policy controls.

A Model Context Protocol server that enables AI assistants like Claude to interact with GitHub repositories, issues, and pull requests.

Enables Large Language Models to analyze GitHub repositories in real-time, providing tools for retrieving repository information, analyzing issues, accessing documentation, and visualizing activity.

A deployable MCP server on Cloudflare Workers that allows you to create custom AI tools without requiring authentication.

Enables AI agents to manage live Firefox tabs and native tab groups via MCP tools over stdio, with exact-match verification and safety constraints. It does not read page content or send browser data remotely.

Enables AI assistants to query and analyze AI agent sessions from observability providers like Shepherd (AIOBS) and Langfuse, allowing users to debug agent runs, compare sessions, track performance, and analyze LLM usage patterns.