The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Azure Devops MCP Onprem
MCP server for on-premises Azure DevOps Server (TFS) with TFVC support - shelvesets, changesets, Work Items, Git, Pipelines, Test Plans, Wiki for AI assistants.
Install
claude mcp add azure-devops --env AZURE_DEVOPS_ENV_FILE=$HOME/.azure-devops-mcp.env -- npx -y @burcusg/azure-devops-mcp-onpremInstall command taken from the project's README or registry entry. Always review code before running it.
README excerpt
Read full README on GitHub →Azure DevOps MCP Server
Governed access to on-prem Azure DevOps (including TFVC) for AI agents and assistants, with typed tools, chainable workflows, and a server-side write-safety layer.
Query work items, repositories, and pipelines in natural language — running locally, no cloud proxy, no telemetry.
Coverage · TFVC · Profiles · Write Safety · Setup
At a glance
| TFVC native | 10 dedicated tools — shelvesets (incl. shelved file content), changesets, diffs, work-item linkage. The reason this server exists. |
| Write safety | 6 layers — MCP annotations · confirmation directive · readonly kill switch · rate limit · dry-run on every write · audit log |
| Local / on-prem only | PAT auth, no cloud proxy, no third-party calls, no telemetry |
| 48 tools / 6 domains | Work Items · Git · TFVC · Pipelines · Wiki · Test Plans |
| Typed results | outputSchema + structuredContent on the 8 most-chained read tools — schema-validated results an agent can chain into the next tool without parsing prose |
@me token |
owner / author / reviewer / assignedTo accept @me — resolved per tenant, stateless for multi-agent setups |
| PR review flow | /review_pull_request → structured advisory review → on request, published to the PR as file-anchored comments, each one confirmed first |
| Profile-based secrets | AZURE_DEVOPS_PROFILE=name → gitignored .env.<name>; no PAT in cloud-synced mcp.json. Multi-instance is a natural byproduct. |
| AI clients | Claude (Code/Desktop), GitHub Copilot, Cursor, Visual Studio Code — any MCP-compatible client |
Example questions
"Show me all active bugs assigned to me in this sprint" "What changed in changeset 12345?" "Review PR 123 and post the findings as comments" "List my latest shelvesets" "Trigger the nightly build on the release branch"
Coverage
One server across the whole development cycle — Plan, Code, Review, Build & Release, Test, Document — with your own templates exposed as MCP resources alongside the built-in tools and prompts. Every write passes a server-side governance layer — readonly mode, dry-run preview, rate limit, and audit log (see Write Safety); tools can also be scoped per role (see Restrict tools per role below).
Full per-tool parameter reference: Tool Reference ↓
Restrict tools per role
Set AZURE_DEVOPS_ENABLED_DOMAINS to a comma-separated list — disabled domains aren't registered, trimming the AI client's tool list and reducing tool-selection confusion. Default loads all 6. get_current_user is core and always registered.
| Role | Domains |
|---|---|
| Project manager | work_items,wiki |
| Developer (TFVC) | work_items,tfvc,pipelines |
| Developer (Git) | work_items,git,pipelines |
| QA / tester | work_items,test_plans,git |
| DevOps / release | work_items,pipelines,git,tfvc |
| Read-only / analyst | work_items,wiki |
Unknown domain names fail at startup — no silent typos. Startup log reports what loaded:
Enabled domains (3/6): work_items, tfvc, pipelines
Disabled domains: git, wiki, test_plans
TFVC support
Similar plugs
Reverse engineer anything with agents, from app behavior down to native binaries.
Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or self-hosted, so teams move from prototype…
An open-source AI agent that brings the power of Gemini directly into your terminal.