"A project management and issue tracking tool" matching MCP servers:

Enables AI assistants to interact with Gitea repositories through intelligent tools for issue/PR management, workflow analysis, compliance checking, and content generation, plus 200+ CLI commands for complete CRUD operations.

MCP server for project management automation, providing tools for project health, documentation, task management, security scanning, and CI/CD validation.

Enables intelligent management of Google Cloud Platform infrastructure using Terragrunt, with support for experimental stacks, parallel deployments, resource visualization, cost analysis, and comprehensive infrastructure operations through natural language.

An MCP server that scaffolds full-stack projects with consistent structure, Docker setup, CI/CD pipelines, and database configuration.

A multi-Jenkins server management and automation tool that enables intelligent scenario mapping, multi-server management, and complete CI/CD lifecycle operations through natural language interactions.

Monitor failing GitHub Actions workflows, auto-fix them with OpenCode, and retry the run — driven by a workflow_run webhook, coordinated through an MCP server.

Automates GitHub issue-to-PR workflows using specialized AI agents (analyst, architect, developer, tester, reviewer) that analyze requirements, design solutions, implement code, generate tests, and perform code reviews with HIPAA compliance checks.

A feature-complete TypeScript project template for rapidly developing Model Context Protocol tools with integrated best practices for code quality, testing, and automated deployment.

Provides structured project management through phase-based workflows, enabling planning, execution tracking, compliance checking, and automated documentation for software development projects.

An interactive tool that enables users to benchmark vLLM endpoints through MCP, allowing performance testing of LLM models with customizable parameters.

Enables AI clients to manage GitLab projects, merge requests, issues, pipelines, wiki, releases, tags, milestones, and repository operations via MCP over stdio, SSE, and Streamable HTTP. Supports personal access token and OAuth authentication plus read-only and modify permission modes.

An MCP server for the GitLab API that enables comprehensive project management, file operations, and issue tracking. It supports automated branch creation, batch file pushes, and interaction with merge requests and CI/CD logs.

HTTP-based MCP server for GitLab API, enabling project management, issue tracking, merge requests, and file operations through natural language.

Audits dbt Core projects for migration blockers and generates actionable guidance for migrating to dbt Cloud, including auto-fixing deprecated syntax.

Enables LLMs to interact with GitHub repositories, issues, pull requests, and workflows through the Model Context Protocol. It provides a comprehensive set of tools for repository management, issue tracking, code search, and CI/CD automation.

Provides AI assistants with access to Capawesome documentation and Cloud management tools, enabling app, build, and deployment operations via API token authentication.

Supply-chain gate for AI agent skills and MCP servers: poison-scan tool definitions, hash-pin the vetted set into a lock file and verify drift in CI. truecopy-mcp is a drop-in stdio proxy that filters a live server's tools/list down to its pinned, unmodified, unpoisoned tools.

Enables a coding agent to answer "is this iOS release ready?" by running read-only App Store Connect checks: build processing, App Review state, a 13-point submission preflight, release-notes policy linting, and App Store Server Notification reconciliation. The lone write capability is a dry-run-first, seven-gate submission tool that always requires explicit confirmation.

Connects AI coding assistants to Gaffer test history and coverage data to analyze project health, debug failures, and identify untested code areas. It enables tools to track test stability, cluster failures by root cause, and monitor code coverage trends across projects.

MCP server with the watch_ci tool that polls GitHub Actions until a commit's CI run finishes, then returns the outcome and failed log tail in one call.

Enables AI assistants to summarize Playwright test runs, identify flaky tests, heuristically triage failures, generate Playwright test stubs, and retrieve recent GitHub CI status through MCP tool calls.

SSWP MCP — Deterministic software attestation for AI-augmented development. Witness any repo through a 5-gate pipeline, adversarially probe dependencies, and produce self-verifying .sswp.json attestations. Fleet registry across 131 nodes with tamper-proof audit ledger and FTS5 search. Agent-native — one tool call from Hermes, Claude, or Cline.

Automates the full setup and deployment of Ballerina + Apache ActiveMQ integrations inside a WSO2 Integrator workspace, from broker validation to a runnable BI-low-code-ready project.

Record an agent's MCP tool-call workflow once, replay it deterministically for zero tokens, and get a receipt — a snapshot-testing and deterministic-execution layer for Agent Skills.

Enables AI agents to interact with Appcircle mobile CI/CD platform for build management, signing identities, testing distribution, and reporting.

AI-powered VMware vSphere with Tanzu (VKS) management. Create and manage Supervisor Namespaces and TanzuKubernetesClusters with 20 MCP tools.

Enables AI agents to deploy, manage, and configure web applications on sota.io, including project creation, deployment, environment variables, custom domains, and rollbacks.

Enables AI coding agents to see their Odoo.sh projects by listing projects, branches and builds, waiting for a build to finish, reading build and server logs, and optionally rebuilding branches or updating the firewall. It runs read-only by default with bounded, time-limited tool calls, keeping the user's Odoo.sh session out of the agent's reach.

Model Context Protocol (MCP) server for GitLab — exposes 1006 GitLab REST & GraphQL API operations as MCP tools (42 meta-tools / 57 enterprise), 24 resources, 38 prompts, and 17 completion types for AI assistants. Written in Go, single static binary, stdio and HTTP transport.

Enables AI agents to set up and operate safe, approval-gated deployments to Plesk servers, including project inspection, deployment-kit generation and validation, status and log checks, and confirmed rollbacks over SSH.