Skip to main content
Glama

Outlook Mail

by io.github.pipeworx-io

Recent Changes

recent_changes
Read-onlyIdempotent

"What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings since since), GDELT→GNews fallback (news mentions in window — GDELT preferred, GNews when rate-limited or 5xx), USPTO (patents granted; PatentsView API sunset May 2025 so this soft-fails until reactivated). since accepts ISO date ("2026-04-01") or relative shorthand ("7d", "30d", "3m", "1y"). Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs. Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesEntity type. Only "company" supported today.
sinceYesWindow start — ISO date ("2026-04-01") or relative ("7d", "30d", "3m", "1y"). Use "30d" or "1m" for typical monitoring.
valueYesTicker (e.g., "AAPL") or zero-padded CIK (e.g., "0000320193").

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already set readOnlyHint, openWorldHint, idempotentHint, and destructiveHint as safe. The description adds valuable behavioral details: parallel call execution, GDELT→GNews fallback, USPTO soft-fail, and citation URIs. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact yet comprehensive, front-loading example queries. Every sentence adds necessary information without redundancy. Efficient use of language.

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?

Despite no output schema, the description specifies the return structure (changes[] grouped by source, total_changes count, citation URIs). It covers source behavior, fallback, caching, and gives a clear alternative tool. Adequate for the tool's complexity.

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?

Schema coverage is 100%, so baseline is 3. The description adds value by explaining the supported entity type, date format options with recommended values, and acceptable input formats for value (ticker or CIK). This enhances usability beyond the schema.

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 the tool provides a change feed for a company over a time window, listing specific sources (SEC EDGAR, GDELT→GNews, USPTO). It distinguishes from the sibling tool entity_profile by specifying when to use the alternative.

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?

The description gives concrete query examples ('What's new with X', 'latest on Y') and explicitly instructs when to use entity_profile instead. It also explains source selection logic, fallback behavior, and date format recommendations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Outlook Mail toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.6/5.0
Disambiguation2/5

The set contains multiple near-duplicate tools: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded overlap heavily (beta is explicitly identical right now), and discover_tools vs suggest_questions both serve a 'what can I do' purpose. The server name 'Outlook Mail' also misleads since only 5 of 36 tools are email-related, creating domain confusion.

Naming Consistency4/5

Most tools follow a readable snake_case verb_noun or prefixed pattern (outlook_list_messages, polymarket_edges, ask_pipeworx). Minor deviations like ai_visibility_check (instead of check_ai_visibility) and pipeworx_feedback/pipeworx_trending (noun-first) are present but don't seriously obscure meaning.

Tool Count2/5

36 tools is well beyond a typical well-scoped set, and the vast majority belong to unrelated Pipeworx/Polymarket domains while the server claims to be Outlook Mail. The count is padded by redundant variants (ask_pipeworx_beta, multiple polymarket scanning tools) that could be consolidated.

Completeness2/5

For the stated Outlook Mail purpose, the surface is read-only: you can list, search, and get messages/profile/folders, but there is no send, reply, delete, move, or mark-as-read capability—an obvious dead end for email workflows. The broader data-research side is more extensive but still lacks update paths for subscriptions/memories.

Resources