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Azure DevOps MCP Server

Node.js TypeScript MCP Azure DevOps License: MIT Tools npm version

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

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


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

DevOps lifecycle coverage — Plan: Work Items · Code: Git, TFVC · Review: Pull Requests, Comments · Build & Release: Pipelines · Test: Test Plans · Document: Wiki

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

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:

  • Shelvesetstfvc_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)
  • Changesetstfvc_list_changesets, tfvc_get_changeset (incl. linked work items), tfvc_get_changeset_changes
  • Browse, files & diffstfvc_browse, tfvc_get_file (at any changeset version), tfvc_get_file_diff (changed hunks between two changesets)
  • Work-item linkageget_work_item_changesets (all TFVC changesets touching a work item, with file contents)

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


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.mdtemplate: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.


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?".


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).


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.


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.


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

One-click install in VS Code

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/acmeacme); override with AZURE_DEVOPS_SERVER_NAME.


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

@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.


Development

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

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.

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MCP server for on-premises Azure DevOps Server (TFS) with TFVC support - shelvesets, changesets, Work Items, Git, Pipelines, Test Plans, Wiki for AI assistants.

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