Skip to main content
Glama

tasks_search

Read-onlyIdempotent

Search your Microsoft To Do and Planner tasks by matching substrings in title or body preview. Filter by source (all, todo, planner) and limit results.

Instructions

Case-insensitive substring search across the user's To Do tasks and Planner tasks. Matches against title and body_preview. source narrows to a single surface — 'all' (default), 'todo', or 'planner'. Returns up to limit matches in the unified envelope shape. Read-only. Note: implementation is client-side because neither surface exposes a server-side $search for tasks; performance is fine at typical task volumes (hundreds, not hundreds of thousands).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
sourceNoall
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint. The description adds valuable context: the search is client-side due to lack of server-side $search, and performance is fine for typical volumes. This goes beyond the annotations and helps set expectations.

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 reasonably concise, front-loading the core purpose and then adding parameter details and behavioral notes. Every sentence adds value, though it could be slightly shorter. It is well-structured and readable.

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 presence of an output schema, annotations covering safety and idempotency, and the description covering parameters and client-side behavior, the description is fully complete for an agent to understand and invoke the tool correctly.

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 input schema has 0% description coverage, but the description details the meaning of each parameter: 'query' is the substring, 'source' narrows to todo/planner/all, 'limit' caps results. This adds necessary semantics beyond the raw schema types.

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 performs a 'case-insensitive substring search' across tasks from To Do and Planner, matching against 'title' and 'body_preview'. It distinguishes itself from sibling tools like 'tasks_assigned_to_me' or 'planner_tasks' by being a search operation, and mentions parameters like 'source' and 'limit'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains when to use the tool (search across tasks) and notes it is read-only. It provides context on the client-side implementation and performance expectations. However, it does not explicitly mention when not to use it or list alternative tools, though sibling names are provided separately.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/XMV-Solutions-GmbH/microsoft-tasks-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server