Azure Devops MCP Onprem

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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

</div> <p align="center"> <img src="docs/demo.gif" alt="An AI assistant explains what a TFVC changeset changed — chaining changeset and work-item tools to report the changed files and the linked bug — then adds a lesson-learned note and resolves that bug, with dry-run preview and audit logging on writes" width="720"> </p>

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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"

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Coverage

<p align="center"> <img src="docs/sdlc-ring.svg" alt="DevOps lifecycle coverage — Plan: Work Items · Code: Git, TFVC · Review: Pull Requests, Comments · Build & Release: Pipelines · Test: Test Plans · Document: Wiki" width="640"> </p>

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

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TFVC support

The reason this server exists. Cloud Azure DevOps disabled new TFVC repos in February 2017, and Microsoft's official MCP server doesn't cover TFVC. If your team is still on Team Foundation Version Control, this is the only MCP server that exposes it natively to AI assistants.

10 dedicated TFVC tools:

• Shelvesets — tfvc_list_shelvesets, tfvc_get_shelveset (file changes + work item links), tfvc_get_shelveset_file (shelved, not-yet-checked-in file content — AI review before check-in, a workflow TFVC never had)
• Changesets — tfvc_list_changesets, tfvc_get_changeset (incl. linked work items), tfvc_get_changeset_changes
• Browse, files & diffs — tfvc_browse, tfvc_get_file (at any changeset version), tfvc_get_file_diff (changed hunks between two changesets)
• Work-item linkage — get_work_item_changesets (all TFVC changesets touching a work item, with file contents)

Filters accept @me where relevant. Requires Code (read & write) PAT scope.

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Prompts & Resources

Prompts are reusable, advisory workflows surfaced as slash commands in the AI client. Each one instructs the model to gather evidence with the read tools and ground every claim in concrete IDs — producing the report never calls a write tool. One exception by design: review_pull_request can afterwards publish its findings as file-anchored PR comments, but only when you explicitly ask, with every comment confirmed before posting. Prompts load on the same domain axis as tools, so disabling a domain hides its prompts.

Domain	Prompt	What it does
git	lessons_learned_git	Root cause / detection / prevention report for a resolved bug, from its history and linked Git commits/PRs
git	my_review_queue	Active PRs assigned to me as a reviewer, project-wide, oldest first (no arguments)
git	summarize_pull_request	Plain-language "what this PR does" summary
git	review_pull_request	Structured advisory review: risks, test gaps, maintainability, questions — on request, publishes findings to the PR as file-anchored comments
git	analyze_commit_range	Release-notes style changelog between two branches
tfvc	lessons_learned_tfvc	Root cause / detection / prevention report for a resolved bug, from its history and linked TFVC changesets
tfvc	changeset_summary	Purpose, files, and scope/risk of a TFVC changeset
work_items	work_item_report	Counts by area + monthly timeline + AI-grouped recurring themes for a work-item filter (titleContains/area/workItemTypes/days)

lessons_learned is split per backend (Git vs. TFVC) so each variant names its own read tools; both need work_items enabled to read the bug itself.

The table lists 8; a 9th prompt, risk_impact_analysis, is conditional — it appears only when a risk-impact.md template is present (see External resources below).

External resources

Point AZURE_DEVOPS_RESOURCE_DIR at a folder and every *.md file in it is exposed as an MCP resource at template:<filename> (e.g. release-checklist.md → template:release-checklist; the filename is URI-encoded, so spaces are safe). Use this to share team templates and checklists with the AI without baking them into the server.

One template is wired to a prompt: dropping a risk-impact.md file in that folder enables the conditional risk_impact_analysis prompt, which fills the template from work-item evidence — optionally weighing an actual pending change via its shelvesetName argument. No template file → the prompt simply doesn't appear.

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Profile-based secrets

mcp.json configs sync to the cloud (Claude Desktop, VS Code Settings Sync), get pasted into tickets, end up in dotfile repos. Inlining AZURE_DEVOPS_PAT there is one git add . away from a public leak.

The convention: set AZURE_DEVOPS_PROFILE=name in mcp.json, keep credentials in a gitignored .env.<name> next to the binary. The server resolves the profile name to that file path; mcp.json stays free of secrets and is safe to commit.

.env.product-a (gitignored):

AZURE_DEVOPS_ORG_URL=https://tfs-1.example.com/tfs/ProductACollection
AZURE_DEVOPS_PROJECT=Product A
AZURE_DEVOPS_PAT=<pat-for-product-a>
# Optional per-profile domain restriction
AZURE_DEVOPS_ENABLED_DOMAINS=work_items,tfvc,pipelines

mcp.json (commitable):

{
  "mcpServers": {
    "ado-product-a": {
      "command": "node",
      "args": ["/path/to/dist/index.js"],
      "env": { "AZURE_DEVOPS_PROFILE": "product-a" }
    }
  }
}

Multi-instance

Once profiles are in place, running multiple ADO instances side-by-side is just adding entries. Each one loads its own .env.<profile> — own PAT, own project, own domain restriction. Per-process state means audit logs, rate limit counters, and @me identity caches never cross between tenants.

{
  "mcpServers": {
    "ado-product-a": {
      "command": "node",
      "args": ["/path/to/dist/index.js"],
      "env": { "AZURE_DEVOPS_PROFILE": "product-a" }
    },
    "ado-product-b": {
      "command": "node",
      "args": ["/path/to/dist/index.js"],
      "env": { "AZURE_DEVOPS_PROFILE": "product-b" }
    }
  }
}

Tool names auto-prefix per server — mcp__ado-product-a__list_repositories vs mcp__ado-product-b__list_repositories.

Env file precedence

Set in mcp.json	File loaded
AZURE_DEVOPS_ENV_FILE=/abs/path	That exact path
AZURE_DEVOPS_PROFILE=name	<projectRoot>/.env.name
(neither)	<projectRoot>/.env

Variables set directly in mcp.json's env block always win over file contents.

Each instance's startup log line env file: ... confirms which file was loaded — handy for debugging "which profile did this tool actually call?".

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Write Safety

Six layers. The LLM cannot bypass the server-side ones — they short-circuit before any API call fires.

Layer	Scope	Enable
MCP annotations	All 48 tools tagged with readOnlyHint / destructiveHint / idempotentHint — clients can skip read confirmations, warn on destructive writes	Always on
Confirmation directive	Every write's description tells the LLM to show payload and ask before calling	Always on
Readonly mode	Server refuses all 8 write tools with a clear error; reads unaffected. CI, demos, sandbox, emergency stop	AZURE_DEVOPS_MODE=readonly
Rate limit	Global sliding 60s window across all writes — runaway-loop fence, not a throughput regulator	AZURE_DEVOPS_RATE_LIMIT_WRITES_PER_MIN=10 (default; 0 disables)
Dry-run	All 8 write tools — pass dryRun: true for the literal API payload without firing; update_work_item also returns the current values next to the intended ones	Per-call
Audit log	JSONL append per write: timestamp, tool, user, input, result, dryRun, ok, durationMs, blocked reason. Each process opens with a session_start header (version, mode, domains, rate limit) so the file interprets itself	AZURE_DEVOPS_AUDIT_LOG=/path/to/audit.jsonl

Audit privacy: add AZURE_DEVOPS_AUDIT_REDACT=1 to keep numeric IDs and field shape but drop all string values (titles, comments, branch names). Useful when work-item content carries classified data.

Plus baseline hardening: WIQL injection sanitization, scrubbed errors (no internal paths/URLs/stack traces in client output), bounded pagination (1-1000).

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Privacy & data flow

The server runs entirely locally. ADO API calls go straight from your machine to your Azure DevOps Server. No telemetry, no phone-home, no cloud proxy, no shared analytics.

External destinations are limited to:

1. Your Azure DevOps Server — the URL in your .env.
2. Your AI assistant (Claude, GitHub Copilot, Cursor) — the AI client reads tool outputs as conversation context per its own privacy policy. The MCP server itself never talks to these services.

Data	Leaves your machine?
PAT	❌ Never — stays in gitignored .env / .env.<profile>
Work items, code, commits, shelvesets	➡ Your ADO Server, then back to your AI assistant
Server / URL / project names	➡ Your AI assistant as part of tool outputs
Usage metrics, error logs	❌ No collection

Every network call is visible in src/ — they all route through azure-devops-node-api pointed at your configured URL.

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Cloud (Azure DevOps Services)

Technically works against dev.azure.com, but this server isn't positioned for cloud:

• TFVC doesn't exist on cloud — disabled for new orgs since February 2017.
• PAT-only auth — many cloud tenants require Microsoft Entra ID, which this server doesn't yet support.
• Microsoft ships @azure-devops/mcp for cloud — officially maintained, Entra ID, broader cloud-specific coverage.

Use this server against cloud only if you specifically need @me, profile-based multi-tenant config, or a tool the official server lacks.

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Setup

Pick one path:

• Quick Start — run from npm, no clone. ~2 minutes.
• Enterprise Setup — clone, build, pin a commit. For air-gapped or audited environments.

Prerequisites

• Node.js ≥ 18
• Azure DevOps Server 2022.2 (tested; older versions with REST API 7.x likely work but untested)
• PAT with the scopes below. Grant only what you need — omitted scopes make the affected tools fail at call time, but the server still starts.

Scope	For
Work Items (read & write)	Work item tools, WIQL queries, statistics
Code (read & write)	Git tools, TFVC tools, PR creation
Build (read & execute)	Pipeline tools, queue_build
Release (read)	Release listing
Test Management (read & write)	Test plans, suites, runs, results; add test cases to a suite
Wiki (read)	Wiki tools

Create the PAT at https://<your-tfs>/_usersSettings/tokens. Set an expiration ≤ 90 days and rotate regularly.

Quick Start (npm)

No public npm access? Skip to Enterprise Setup — it builds from source and can use an internal npm mirror.

1. Credential file — create ~/.azure-devops-mcp.env (Linux/macOS) or C:\Users\you\.azure-devops-mcp.env (Windows):

AZURE_DEVOPS_ORG_URL=https://your-tfs-server/tfs/YourCollection
AZURE_DEVOPS_PROJECT=YourProjectName
AZURE_DEVOPS_PAT=your_pat_token
# AZURE_DEVOPS_SSL_IGNORE=true   # uncomment for self-signed certs

2. Register with your AI client. Shortest paths:

VS Code — one-click install

<p align="center"> <a href="https://insiders.vscode.dev/redirect/mcp/install?name=azure-devops-mcp-onprem&config=%7B%22type%22%3A%22stdio%22%2C%22command%22%3A%22npx%22%2C%22args%22%3A%5B%22-y%22%2C%22%40burcusg%2Fazure-devops-mcp-onprem%22%5D%2C%22env%22%3A%7B%22AZURE_DEVOPS_ENV_FILE%22%3A%22%24%7BuserHome%7D%2F.azure-devops-mcp.env%22%7D%7D"> <img src="https://img.shields.io/badge/%E2%96%B6%20ONE--CLICK%20INSTALL%20IN%20VS%20CODE-007ACC?style=for-the-badge&logo=visualstudiocode&logoColor=white&labelColor=1A1A2E&logoWidth=30" alt="One-click install in VS Code" height="55"> </a> </p>

Claude Code — one command

claude mcp add azure-devops --env AZURE_DEVOPS_ENV_FILE=$HOME/.azure-devops-mcp.env -- npx -y @burcusg/azure-devops-mcp-onprem

Other clients (Claude Desktop / Cursor / Antigravity / Codex CLI)

JSON config — see Configure AI client below.

Enterprise Setup (clone)

git clone https://github.com/burcusipahioglu/azure-devops-mcp-onprem.git
cd azure-devops-mcp-onprem
npm install
npm run build
cp .env.example .env       # copy .env.example .env on Windows
# fill in .env with your TFS details
npm start                  # smoke-test the connection — Ctrl+C to stop

Expected stderr on startup:

Azure DevOps MCP Server "CompanyOrg" running on stdio
env file: /path/to/.env
Enabled domains (6/6): work_items, git, tfvc, pipelines, wiki, test_plans
External resources loaded: 0
Authenticated as: Your Name (your.email@company.com)

Then point your AI client at dist/index.js (see below). No env block needed — the server reads .env from the repo root.

Configure AI client

⚠ Never inline AZURE_DEVOPS_PAT / AZURE_DEVOPS_ORG_URL / AZURE_DEVOPS_PROJECT in client configs. Client configs sync to the cloud (Claude Desktop sync, VS Code Settings Sync) or get pasted into tickets. Use AZURE_DEVOPS_ENV_FILE (Quick Start) or .env in the repo (Enterprise Setup). For multiple TFS instances see Profile-based secrets.

Client	Path
VS Code	Includes .vscode/mcp.json. Copilot Chat → Agent mode (Ctrl+Shift+I)
GitHub Copilot CLI	/mcp add (interactive) or edit ~/.copilot/mcp-config.json
Claude Code	claude mcp add azure-devops -- node /path/to/dist/index.js
Claude Desktop	Edit %APPDATA%\Claude\claude_desktop_config.json (Windows) / ~/Library/Application Support/Claude/claude_desktop_config.json (macOS)
Cursor / Antigravity / Codex CLI	Standard MCP JSON config — same shape as Claude Desktop

Enterprise Setup config template (any client):

{
  "mcpServers": {
    "azure-devops": {
      "command": "node",
      "args": ["/absolute/path/to/azure-devops-mcp-onprem/dist/index.js"]
    }
  }
}

Quick Start config template (npm + credential file):

{
  "mcpServers": {
    "azure-devops": {
      "command": "npx",
      "args": ["-y", "@burcusg/azure-devops-mcp-onprem"],
      "env": {
        "AZURE_DEVOPS_ENV_FILE": "C:\\Users\\you\\.azure-devops-mcp.env"
      }
    }
  }
}

Restart the client. All 48 tools appear in the tool picker. Server name is auto-detected from AZURE_DEVOPS_ORG_URL (e.g. https://dev.azure.com/acme → acme); override with AZURE_DEVOPS_SERVER_NAME.

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Tool Reference

Typed results (first wave): query_work_items, list_pull_requests, get_pull_request, get_build, list_builds, tfvc_get_changeset, tfvc_list_changesets, list_test_runs declare an MCP outputSchema and return structuredContent alongside the usual JSON text (text shape unchanged — existing clients see no difference). An agent can feed one tool's structuredContent straight into the next without parsing prose.

Dry-run: every write tool also accepts dryRun: true (not repeated in the tables below).

Work Items (9 tools)

Tool	Description	Key Parameters
query_work_items	Execute a WIQL query (@Me, @CurrentIteration, @Today macros)	query, fields (projection per item), top
get_work_item	Get work item by ID	id, expand (none/relations/fields/links/all)
create_work_item	Create a new work item	type, title, description, assignedTo (accepts @me), areaPath, iterationPath, additionalFields
update_work_item	Update work item fields (returns before/after diff)	id, fields (key-value map)
get_work_item_comments	List comments (paginated, asc/desc, optional rendered HTML)	workItemId, top, order, includeRenderedText, continuationToken
add_work_item_comment	Add a comment	workItemId, text
link_work_items	Link two work items	sourceId, targetId, linkType
get_work_item_history	Full change audit trail (who/what/when with old/new values)	workItemId, top, skip
get_work_item_statistics	Work item counts by area path + monthly timeline (handles 20K+ items)	workItemTypes, days, states, areaPathPrefix, areaPathContains, titleContains, tags, iterationPath, groupByDepth, topAreas

Git (9 tools)

Tool	Description	Key Parameters
list_repositories	List all Git repos in project	—
list_branches	List branches in a repo	repositoryId
get_file_content	Get file content from repo	repositoryId, path, branch
get_file_diff	Unified diff of one file between two branches/commits (changed hunks only)	repositoryId, path, baseVersion, targetVersion, contextLines
list_pull_requests	List PRs; omit repositoryId for project-wide, filter by reviewer (accepts @me)	repositoryId, reviewer, status, top
get_pull_request	Get PR details	repositoryId, pullRequestId
get_pull_request_comments	List PR comment threads (file-anchored + general)	repositoryId, pullRequestId, includeSystem
add_pull_request_comment	Comment on a PR — general, file-anchored (filePath+line), or reply (threadId)	repositoryId, pullRequestId, content, threadId, filePath, line
create_pull_request	Create a new PR	repositoryId, title, sourceBranch, targetBranch

Git Advanced (4 tools)

Tool	Description	Key Parameters
list_commits	Commit history with filters	repositoryId, branch, author (accepts @me), fromDate, toDate, itemPath
get_commit_changes	File changes in a commit	repositoryId, commitId
compare_branches	Branch diff (ahead/behind + changed files)	repositoryId, baseBranch, targetBranch
get_work_item_commits	Git commits & PRs linked to a work item	workItemId, includeChanges

TFVC (10 tools)

Tool	Description	Key Parameters
tfvc_browse	Browse files/folders at a TFVC path	scopePath, recursion
tfvc_get_file	Get file content	path, version (changeset number)
tfvc_get_file_diff	Unified diff of one TFVC file between two changesets (changed hunks only)	path, baseVersion, targetVersion, contextLines
tfvc_get_changeset	Get changeset details	id, includeWorkItems, includeDetails
tfvc_list_changesets	List changesets with filters	itemPath, author (accepts @me), fromDate, toDate, top
tfvc_get_changeset_changes	List file changes in a changeset	changesetId, top
tfvc_list_shelvesets	List shelvesets; pass name+owner to find one in a single call	name, owner (accepts @me), top
tfvc_get_shelveset	Get shelveset details + changes	shelvesetId, includeWorkItems
tfvc_get_shelveset_file	Get shelved (pending) content of one file in a shelveset	shelvesetId, path, maxBytes
get_work_item_changesets	All TFVC changesets linked to a work item (with file changes)	workItemId, includeFileContent, maxFiles

Pipelines (5 tools)

Tool	Description	Key Parameters
list_build_definitions	List pipeline definitions	name, top
queue_build	Trigger a build	definitionId, sourceBranch, parameters
get_build	Get build status	buildId
list_builds	List recent builds	definitionId, status, top
list_releases	List releases	definitionId, top

Core (1 tool, always registered)

Tool	Description	Key Parameters
get_current_user	Identity of the authenticated PAT owner (displayName, id, uniqueName)	—

Test Management (7 tools)

Tool	Description	Key Parameters
list_test_plans	List test plans	filterActivePlans, includePlanDetails
get_test_plan	Get test plan details	planId
list_test_suites	List suites in a test plan	planId, asTreeView
list_test_cases	List test cases in a suite	planId, suiteId
list_test_runs	List test runs (manual/automated)	planId, automated, top
get_test_results	Test results with pass/fail and errors	runId, outcomes, top
add_test_cases_to_suite	Link existing Test Case work items into a suite	planId, suiteId, testCaseIds

Wiki (3 tools)

Tool	Description	Key Parameters
list_wikis	List all wikis (project + code wikis)	—
get_wiki_page	Get page content in Markdown	wikiIdentifier, path, includeChildren
list_wiki_pages	All page paths (TOC) with view stats	wikiIdentifier, top, pageViewsForDays

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@me token

Several filter parameters accept the magic token @me — the server resolves it to the authenticated PAT owner's identity via Azure DevOps ConnectionData (display name for author/owner filters, user id where the API requires one, e.g. reviewer). The identity is cached for the lifetime of the process.

Why: in multi-agent setups, sub-agents rarely know the human's display name. @me lets any agent filter to "my stuff" without needing identity context.

Tool	Parameter
tfvc_list_shelvesets	owner
tfvc_list_changesets	author
list_commits	author
list_pull_requests	reviewer
create_work_item	assignedTo

// "Show me my latest shelveset"
tfvc_list_shelvesets({ owner: "@me", top: 1 })

// "Which commits did I push to feature/login this week?"
list_commits({ repositoryId: "my-repo", branch: "feature/login", author: "@me", fromDate: "2026-04-10" })

WIQL queries (query_work_items) use Azure DevOps' native macros — @Me, @CurrentIteration, @Today — no server-side resolution needed. "My sprint items" is one query away: ... WHERE [System.IterationPath] = @CurrentIteration AND [System.AssignedTo] = @Me.

Need the identity explicitly? Call get_current_user.

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Development

npm run dev      # watch mode
npm run build    # build once
npm start        # start the server

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License

Released under the MIT License. Copyright (c) 2026 Burcu Sipahioglu Gokbulut.

Free to use, modify, and redistribute — commercial or personal — provided the copyright notice and license text are preserved.