"Y Combinator" matching MCP servers:

Compacts noisy test, build, and cloud-log output before an AI agent reads it — dedupes repeats, collapses stack frames, folds Playwright retries, and renders CloudWatch/GCP JSON logs down to the signal. Typically 80–95% fewer tokens on failures. Tool: compact_output. Run: npx -y logslim logslim-mcp

A TypeScript starter template for building Model Context Protocol (MCP) servers with built-in support for tools, testing, and CI/CD pipelines. It provides a complete development environment for creating custom AI assistant integrations for tools like Claude, Copilot, and Cursor.

A secure MCP server providing controlled access to pixi tasks and commands, eliminating agent bash circumvention. It exposes 11 pixi tools through 4 meta-tools for ~95% context savings.

Enables automated Python code quality checks including linting, complexity analysis, typo detection, structure validation, duplicate detection, and test coverage, with integration into Cursor IDE and CLI.

Enables MCP-compatible AI clients to manage GitHub repositories and issues and trigger repository dispatch events via tools and a REST API.

Manages resource allocation, MCP server lifecycle, and Kubernetes workers in cortex automation systems. Provides tools for requesting/releasing job resources, starting/stopping/scaling MCP servers, and provisioning/destroying burst workers with TTL management.

A minimal starter template for building Model Context Protocol (MCP) servers using TypeScript and FastMCP, including an example weather tool for demonstration.

A production-ready template for building Model Context Protocol servers in Python, featuring example tools, structured logging, and multiple transport protocols.

Enables triggering GitHub repository dispatch events, creating issues, and retrieving repository information.

Connects AI assistants to GitLab, enabling natural language queries for merge requests, code reviews, pipeline tests, job logs, and commit discussions directly from chat.

Enables interaction with Azure DevOps, including listing pipelines and runs, viewing logs and artifacts, collecting and normalizing security reports, and triggering pipelines with safety controls.

Unified MCP server for Git forge management across GitHub, GitLab, Gitea, and Bitbucket, enabling repository, issue, PR, and CI/CD operations via CLI tools and APIs.

Enables scanning Python repos for dead code and automatically drafting a branch + PR for the safe subset (unused single-name imports) after running the repo's full test suite. All other findings are reported without modification, and a human always merges.

MCP server for Argo CD and Vault that allows authenticated users to run CLI commands via GitLab SSO, with confirmation for dangerous operations and secret redaction from model context.

Enables CI/CD failure triage for GitHub Actions by inspecting failed runs, classifying root causes with LLM assistance, retrieving relevant runbook guidance, estimating flakiness, and either preparing dry-run fix PRs or publishing structured diagnoses to Discord for human review.

Validates release hygiene in local repositories with network-free, read-only tools for checking repo structure, version alignment, and generating release checklists.

MCP server for Woodpecker CI: read repositories, pipelines and logs, and drive builds, secrets and crons

Enables AI assistants to manage Bitbucket Cloud repositories, pull requests, branches, commits, pipelines, issues, and webhooks through the Model Context Protocol.

A deterministic, network-free MCP server for validating repository release hygiene and version alignment in local projects. It enables automated repository health checks and generates standardized release checklists based on project state.

MCP server for Codecov that provides tools to get commit coverage totals and prompts to suggest tests to write.