"An agent for conducting research" matching MCP servers:

An MCP-style stdio server for evaluating AI agent outputs, enabling CI-friendly quality gates, regression comparisons, and canary promotion decisions.

Enables LLM clients to access DevSecOps tooling such as CI/CD pipeline status, vulnerability triage, log search, and dependency scanning through MCP, turning AI copilots into security-aware engineering partners.

Serves MCP tools to inspect agent trace JSONL files and evaluate them against golden-case constraints, returning structured metrics and gate results.

Remote MCP server for Android CLI agent build gate that enables checking builds, suggesting fixes, explaining permission blockers, issuing receipts, and exporting logs.

A production-grade MCP server with 6 sandboxed tools and an agent orchestration engine for autonomous task completion, featuring an evaluation suite with CI/CD quality gates.

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.

Stops your AI from re-introducing bugs, leaking provider keys, or weakening tests. Bug fixes become permanent regression guards; blocked mistakes become AI lessons the agent reads and learns from before its next edit.

Baron gives an AI coding agent one normalized contract for work orchestration: create and transition issues, cut branches, open and merge pull requests, and read CI and deployment status across Azure DevOps, GitHub and Slack.

Browser acceptance testing for AI agent deliverables: verify agent output in real Chromium from JSON specs, with MCP server, visual regression, multi-browser support and GitHub Actions.

Verify-before-act safety tools for AI coding agents, providing MCP tools to check packages, lockfiles, manifests, and CI workflows for supply chain risks.

Exposes tools to list, run, and inspect GitHub Actions workflows locally via act, enabling debugging and fixing failures through an agent loop.

Governance/control plane for MCP-enabled coding-agent workflows with validation, findings, approvals, budgets, and proof bundles.

MCP server for agent-controlled deployment on Pier, exposing 14 tools mapped to Pier REST API endpoints for managing deployments via stdio or HTTP.

Turns a manager's plain-English goal into a verified, looped, watchable build run driven by the IDE's agent, without SDK.

Deploys projects straight from an AI agent to Snaphost and returns a public URL, with automatic Dockerfile generation, build/run/log management, and deploy lifecycle control.

Self-hosted coding agent that runs Claude Code or Codex in your own infrastructure and works from Slack. Exposes codebase investigation, file edits, branch and PR creation, allowlisted command execution, CI status and an audit log as MCP tools, keeping every credential behind the tool layer instead of handing it to the model.

Enables AI clients to analyze software test results and defect records, producing explainable GO, CONDITIONAL_GO, or NO_GO release-readiness recommendations with deterministic risk scoring, failed-test retrieval, defect hotspot ranking, and regression test planning.

Integrates Cline with Azure DevOps services, enabling access to work items, repositories, and pull requests through configurable MCP tools.

Enables intelligent access to AL-Go documentation, workflows, and domain expertise for Business Central development automation through specialized personas and cross-source semantic search.

MCP server for end-to-end QA automation: generates test scenarios, discovers Playwright locators, creates TypeScript test code, executes tests, and creates GitHub issues for failures.