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S2thend

cursor-history-mcp

cursor_history_search

Search through all Cursor AI chat sessions to find specific keywords or phrases, returning matching sessions with surrounding context for efficient retrieval.

Instructions

Search across all Cursor AI chat sessions for a keyword or phrase. Returns matching sessions with context around each match.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe search query (keyword or phrase to find)
limitNoMaximum number of results to return (default: 10)
contextNoNumber of characters of context to show around each match (default: 50)
Behavior3/5

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

With no annotations, the description carries the full burden. It describes a read-only search operation, which is adequate, but it does not disclose any limitations, performance characteristics, or permissions required. The description is factual but minimal.

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 a single, well-structured sentence that efficiently communicates the tool's purpose and output. Every word contributes value, and there is no unnecessary verbosity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple search tool with three parameters and no output schema, the description provides the essential information: what it searches and what it returns. While it does not detail the exact return format, the phrase 'matching sessions with context around each match' gives sufficient guidance for an agent to understand the output.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema fully documents each parameter's purpose and constraints. The description does not add any additional semantic information beyond summarizing the parameters, thus the baseline score of 3 is appropriate.

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 verb 'Search' and the resource 'all Cursor AI chat sessions', specifying it finds a keyword or phrase and returns matching sessions with context. This is distinct from siblings like cursor_history_list (likely lists all sessions) or cursor_history_show (shows a specific session), making the tool's purpose unambiguous.

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

Usage Guidelines3/5

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

The description implies usage for searching chat history but does not provide explicit guidance on when to use this tool versus alternatives like cursor_history_list or cursor_history_show. No when-not or alternatives are mentioned, leaving the agent to infer from context.

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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