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jonnybottles

M365 Roadmap MCP Server

by jonnybottles
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

search_roadmap

Find Microsoft 365 roadmap features using keyword, product, status, cloud, and date filters. Track recent additions and updates with flexible search.

Instructions

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")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results to return (default: 10, max: 100). Ignored when feature_id is provided.
queryNoOptional keyword to match against title and description (case-insensitive).
statusNoOptional status filter. Valid values: In development, Rolling out, Launched.
productNoOptional product tag to filter by (case-insensitive partial match, e.g. "Teams" matches "Microsoft Teams").
platformNoOptional platform filter (case-insensitive partial match).
feature_idNoOptional roadmap ID to retrieve a single specific feature. When provided, all other filters are ignored.
preview_dateNoOptional preview availability date filter (partial string match against previewAvailabilityDate, e.g. "2026-07").
rollout_dateNoOptional rollout date filter (partial string match against generalAvailabilityDate, e.g. "2026-03").
release_phaseNoOptional release phase filter (case-insensitive partial match).
cloud_instanceNoOptional cloud instance filter (case-insensitive partial match, e.g. "GCC" matches "GCC", "GCC High" matches "GCC High").
include_facetsNoWhen 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_daysNoOptional 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_daysNoOptional number of days to look back for recently modified features (clamped to 1-365).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Tool Definition Quality

A4.8/5.0
Behavior5/5

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.

Conciseness4/5

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.

Completeness5/5

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.

Parameters4/5

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.

Purpose5/5

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.

Usage Guidelines5/5

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.

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