M365 Roadmap MCP Server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@M365 Roadmap MCP ServerShow me recent SharePoint roadmap updates."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Disclaimer: This is an independent, self-built project and is not an official Microsoft tool or service.
M365 Roadmap MCP Server
A Python-based MCP (Model Context Protocol) server that enables AI agents to query the Microsoft 365 Roadmap programmatically.
Strategic Rationale
For organizations relying on Microsoft 365, Teams, or SharePoint, the "Roadmap" is the single source of truth for upcoming changes. However, navigating the roadmap website manually is cumbersome and disconnected from technical planning workflows. "When is Copilot coming to GCC High?" is a question that affects multi-million dollar contracts and deployment schedules.
Existing research indicates that while RSS feeds exist, there is no tool that allows an AI agent to structurally query this data to answer complex filtering questions. A "Roadmap Scout" MCP server empowers the Agent to act as a release manager, proactively identifying features that enable new capabilities or threaten existing customizations.
Related MCP server: Microsoft MCP
Prompt Examples
Once connected to an MCP client, you can ask questions like:
Search by product and status: "What Microsoft Teams features are currently rolling out?"
Check government cloud availability: "Is Copilot available for GCC High yet?"
Find recent additions: "Show me everything added to the M365 roadmap in the last 30 days"
Get feature details: "Tell me more about roadmap feature 534606"
Government cloud planning: "My agency is on GCC High. Which OneDrive features can we expect?"
Installation
Prerequisites
Python 3.11+
An MCP-compatible client (Claude Desktop, Cursor, Claude Code, GitHub Copilot CLI, etc.)
From PyPI (recommended)
Using uvx (requires uv):
uvx m365-roadmap-mcpTo update to the latest version:
uvx m365-roadmap-mcp@latestInstall uv if you don't have it:
# macOS / Linux
curl -LsSf https://astral.sh/uv/install.sh | sh
# Windows (PowerShell)
irm https://astral.sh/uv/install.ps1 | iexOr install with pip (no uv required):
pip install m365-roadmap-mcp
# Update to latest
pip install --upgrade m365-roadmap-mcpQuick Setup
One-click install: Click VS Code badge for automatic setup (requires
uvinstalled) Manual install: See instructions below for Cursor, Claude Code, Copilot CLI, or Claude Desktop
Client Configuration
Running the server
uvx m365-roadmap-mcpOr if installed with pip:
m365-roadmap-mcpClaude Desktop
Add to your Claude Desktop MCP config:
macOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonWindows:
%APPDATA%\Claude\claude_desktop_config.json
Using uvx (recommended)
{
"mcpServers": {
"m365-roadmap": {
"command": "uvx",
"args": ["m365-roadmap-mcp"]
}
}
}Using installed package
{
"mcpServers": {
"m365-roadmap": {
"command": "m365-roadmap-mcp"
}
}
}Cursor
Option 1: One-Click Install (Recommended)
cursor://anysphere.cursor-deeplink/mcp/install?name=m365-roadmap-mcp&config=eyJjb21tYW5kIjogInV2eCIsICJhcmdzIjogWyJtMzY1LXJvYWRtYXAtbWNwIl19Option 2: Manual Configuration
Add to your Cursor MCP config:
macOS:
~/Library/Application Support/Cursor/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.jsonWindows:
%APPDATA%\Cursor\User\globalStorage\saoudrizwan.claude-dev\settings\cline_mcp_settings.json
Claude Code
claude mcp add --transport stdio m365-roadmap -- uvx m365-roadmap-mcpGitHub Copilot CLI
Add to ~/.copilot/mcp-config.json:
{
"mcpServers": {
"m365-roadmap": {
"type": "stdio",
"command": "uvx",
"args": ["m365-roadmap-mcp"]
}
}
}Features
Provides a single search_roadmap tool that handles all M365 roadmap queries. Combine any filters:
Keyword search -- Find features by keyword in title/description
Product filter -- Filter by product tag (Teams, SharePoint, etc.)
Status filter -- Filter by status (In development, Rolling out, Launched)
Cloud instance filter -- Filter by cloud instance (GCC, GCC High, DoD)
Feature lookup -- Retrieve full metadata for a specific roadmap ID
Recent additions -- List features added within the last N days
Release phase filter -- Filter by release phase (General Availability, Preview, Targeted Release)
Platform filter -- Filter by platform (Web, Desktop, iOS, Android, Mac)
Rollout date filter -- Filter by general availability date (e.g., "2026-03", "2026")
Preview date filter -- Filter by preview availability date (e.g., "2026-07", "2026")
Recently modified -- List features modified within the last N days
Data Source
This MCP server pulls data from Microsoft's public roadmap API:
API Endpoint:
https://www.microsoft.com/releasecommunications/api/v2/m365Authentication: None required (public endpoint)
RSS Mirror:
https://www.microsoft.com/microsoft-365/RoadmapFeatureRSS(same data, RSS format)
This is the same data that powers the Microsoft 365 Roadmap website. The legacy endpoint (roadmap-api.azurewebsites.net) was retired in March 2025.
Coverage and Limitations
The API returns approximately 1,900 active features -- those currently In Development, Rolling Out, or recently Launched. This is a hard cap; older or retired features age out of the API and are no longer returned. The roadmap website may display historical features that are no longer present in the API.
License
MIT
Available Tools
1 toolsearch_roadmapA
Search the Microsoft 365 Roadmap for features matching keywords and filters.
Combines keyword search, product filtering, status filtering, cloud instance filtering, and recency filtering into a single flexible tool. All filter parameters are optional and can be combined. When no filters are provided, returns the most recent features.
Use this tool to:
Browse recent roadmap features (no filters)
Search for features by keyword (query="Copilot")
Filter by product (product="Microsoft Teams")
Find features by status (status="In development", "Rolling out", "Launched")
Filter by cloud instance (cloud_instance="GCC High", "DoD", "GCC")
Retrieve a specific feature by ID (feature_id="534606")
List recently added features (added_within_days=30)
Filter by release phase (release_phase="General Availability", "Preview")
Filter by platform (platform="Web", "iOS", "Android")
Filter by rollout date (rollout_date="2026-03")
Filter by preview date (preview_date="2026-07")
List recently modified features (modified_within_days=7)
Combine any of the above (query="Copilot" + product="Teams" + cloud_instance="GCC")
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of results to return (default: 10, max: 100). Ignored when feature_id is provided. | |
| query | No | Optional keyword to match against title and description (case-insensitive). | |
| status | No | Optional status filter. Valid values: In development, Rolling out, Launched. | |
| product | No | Optional product tag to filter by (case-insensitive partial match, e.g. "Teams" matches "Microsoft Teams"). | |
| platform | No | Optional platform filter (case-insensitive partial match). | |
| feature_id | No | Optional roadmap ID to retrieve a single specific feature. When provided, all other filters are ignored. | |
| preview_date | No | Optional preview availability date filter (partial string match against previewAvailabilityDate, e.g. "2026-07"). | |
| rollout_date | No | Optional rollout date filter (partial string match against generalAvailabilityDate, e.g. "2026-03"). | |
| release_phase | No | Optional release phase filter (case-insensitive partial match). | |
| cloud_instance | No | Optional cloud instance filter (case-insensitive partial match, e.g. "GCC" matches "GCC", "GCC High" matches "GCC High"). | |
| include_facets | No | When True, includes taxonomy facets (products, statuses, release_rings, platforms, cloud_instances) with occurrence counts in the response. Use with limit=0 to get only facets without features. Facets are computed from matched results after filters are applied. | |
| added_within_days | No | Optional number of days to look back for recently added features (clamped to 1-365). Only features with a created date within this window are returned. | |
| modified_within_days | No | Optional number of days to look back for recently modified features (clamped to 1-365). |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does so excellently. It discloses key behaviors such as all filters being optional and combinable, feature_id being exclusive, partial matching for dates, and include_facets behavior with limit=0. This is substantial contextual detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is longer than average but well-organized: a summary paragraph followed by a categorized bullet list of use cases. Each line is purposeful and adds specific guidance, though it could be tightened slightly without losing meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (13 optional parameters, output schema, no annotations), the description covers all essential contexts: navigation, filtering, special cases, and combination examples. The presence of an output schema means return-value details are handled elsewhere, so nothing critical is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides 100% coverage with descriptions for every parameter, so baseline is 3. The description adds value by offering concrete usage examples (e.g., query='Copilot', product='Microsoft Teams') and clarifying combinability, which elevates it above the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search the Microsoft 365 Roadmap for features matching keywords and filters' with a specific verb and resource. It also enumerates many distinct capabilities (keyword, product, status, cloud instance, feature_id, etc.) that differentiate it from generic search tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides an explicit 'Use this tool to' list with concrete examples for each filter type, plus guidance on how filters combine and the default behavior when no filters are given. This gives the agent clear directives for when to invoke the tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
1 tool update
v0.4.0- First observed
search_roadmap
TDQS
Only one tool exists, so there is no possibility of confusing it with other tools. The tool's purpose is clear and unique, making disambiguation trivially perfect.
The single tool name 'search_roadmap' follows a consistent verb_noun pattern, which is predictable and clear. With only one tool, the naming is internally consistent.
While a single tool is at the low end of the range, it comprehensively covers the server's stated purpose of searching the M365 Roadmap. The tool is highly flexible with many optional filters, making the count appropriate for its narrow scope.
The search tool covers all expected operations for a roadmap lookup: browsing recent features, searching by keyword, filtering by product/status/cloud/date, and retrieving by specific ID. There are no obvious gaps for a read-only roadmap search service.
Maintenance
Resources
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