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vltansky

Cursor Conversations MCP Server

search_conversations

Search Cursor chat content using exact text matching to find discussions containing specific technical terms, error messages, or code patterns.

Instructions

Searches through Cursor chat content using exact text matching (NOT semantic search) to find relevant discussions. WARNING: For project-specific searches, use list_conversations with projectPath instead of this tool! This tool is for searching message content, not project filtering.

WHEN TO USE THIS TOOL:

  • Searching for specific technical terms in message content (e.g., "useState", "async/await")

  • Finding conversations mentioning specific error messages

  • Searching for code patterns or function names

WHEN NOT TO USE THIS TOOL:

  • ❌ DON'T use query="project-name" - use list_conversations with projectPath instead

  • ❌ DON'T search for project names in message content

  • ❌ DON'T use this for project-specific filtering

Search methods (all use exact/literal text matching):

  1. Simple text matching: Use query parameter for literal string matching (e.g., "react hooks")

  2. Multi-keyword: Use keywords array with keywordOperator for exact matching

  3. LIKE patterns: Advanced pattern matching with SQL wildcards (% = any chars, _ = single char)

  4. Date range: Filter by message timestamps (YYYY-MM-DD format)

IMPORTANT: When using date filters, call get_system_info first to know today's date.

Examples: likePattern="%useState(%" for function calls, keywords=["typescript","interface"] with AND operator.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoExact text matching - searches for literal string occurrences in MESSAGE CONTENT (e.g., "react hooks", "useState", "error message"). ❌ DON'T use for project names - use list_conversations with projectPath instead!
keywordsNoArray of keywords for exact text matching - use with keywordOperator to find conversations with specific combinations
keywordOperatorNoHow to combine keywords: "AND" = all keywords must be present, "OR" = any keyword can be presentOR
likePatternNoSQL LIKE pattern for advanced searches - use % for any characters, _ for single character. Examples: "%useState(%" for function calls, "%.tsx%" for file types
startDateNoStart date for search (YYYY-MM-DD). Note: Timestamps may be unreliable.
endDateNoEnd date for search (YYYY-MM-DD). Note: Timestamps may be unreliable.
searchTypeNoFocus search on specific content types. Use "project" for project-specific searches that leverage file path context.all
maxResultsNoMaximum number of conversations to return
includeCodeNoInclude code blocks in search results
outputModeNoOutput format: "json" for formatted JSON (default), "compact-json" for minified JSONjson
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively explains the search method (exact text matching, NOT semantic search), provides warnings about unreliable timestamps, and mentions the need to call 'get_system_info' for date context. However, it doesn't fully describe return format or pagination behavior, leaving some gaps.

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 well-structured with clear sections (warning, usage guidelines, search methods, examples) and uses formatting effectively. While comprehensive, some sentences could be more concise, and the warning is repeated multiple times, slightly reducing efficiency.

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 10-parameter search tool with no annotations and no output schema, the description does an excellent job covering purpose, usage, and parameter semantics. It provides concrete examples and warnings. The main gap is the lack of information about return values or result format, which would be helpful given the absence of an output schema.

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 description coverage is 100%, so the baseline is 3. The description adds significant value by explaining the four search methods (simple text matching, multi-keyword, LIKE patterns, date range) with concrete examples and clarifying the relationship between parameters. This goes well beyond what the schema provides in isolation.

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 'searches through Cursor chat content using exact text matching' and distinguishes it from sibling tools by explicitly warning against using it for project-specific searches, directing users to 'list_conversations with projectPath instead'. This provides specific verb+resource+scope and clear sibling differentiation.

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 includes explicit 'WHEN TO USE THIS TOOL' and 'WHEN NOT TO USE THIS TOOL' sections with concrete examples and clear exclusions. It names the alternative tool ('list_conversations') and provides specific guidance on what queries to avoid, making it highly actionable for an AI agent.

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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