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think

Log and organize detailed thought processes for code-related tasks like debugging, refactoring, or feature design without altering the repository. Use for brainstorming solutions, hypothesis testing, or planning implementation strategies.

Instructions

Use the tool to think about something. It will not obtain new information or make any changes to the repository, but just log the thought. Use it when complex reasoning or brainstorming is needed. Ensure thinking content is concise and accurate, without needing to include code details

Common use cases:

  1. When exploring a repository and discovering the source of a bug, call this tool to brainstorm several unique ways of fixing the bug, and assess which change(s) are likely to be simplest and most effective

  2. After receiving test results, use this tool to brainstorm ways to fix failing tests

  3. When planning a complex refactoring, use this tool to outline different approaches and their tradeoffs

  4. When designing a new feature, use this tool to think through architecture decisions and implementation details

  5. When debugging a complex issue, use this tool to organize your thoughts and hypotheses

  6. When considering changes to the plan or shifts in thinking that the user has not previously mentioned, consider whether it is necessary to confirm with the user.

<think_example> Feature Implementation Planning

  • New code search feature requirements:

  • Search for code patterns across multiple files

  • Identify function usages and references

  • Analyze import relationships

  • Generate summary of matching patterns

  • Implementation considerations:

  • Need to leverage existing search mechanisms

  • Should use regex for pattern matching

  • Results need consistent format with other search methods

  • Must handle large codebases efficiently

  • Design approach:

  1. Create new CodeSearcher class that follows existing search patterns

  2. Implement core pattern matching algorithm

  3. Add result formatting methods

  4. Integrate with file traversal system

  5. Add caching for performance optimization

  • Testing strategy:

  • Unit tests for search accuracy

  • Integration tests with existing components

  • Performance tests with large codebases </think_example>

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
thoughtYesThe detailed thought process to record

Implementation Reference

  • Core handler function that executes the 'think' tool logic: extracts and validates the 'thought' parameter, logs it using tool_ctx.info, and returns a confirmation message without performing any external actions.
    async def call( self, ctx: MCPContext, **params: Unpack[ThinkingToolParams], ) -> str: """Execute the tool with the given parameters. Args: ctx: MCP context **params: Tool parameters Returns: Tool result """ tool_ctx = create_tool_context(ctx) tool_ctx.set_tool_info(self.name) # Extract parameters thought = params.get("thought") # Validate required thought parameter if not thought: await tool_ctx.error( "Parameter 'thought' is required but was None or empty" ) return "Error: Parameter 'thought' is required but was None or empty" if thought.strip() == "": await tool_ctx.error("Parameter 'thought' cannot be empty") return "Error: Parameter 'thought' cannot be empty" # Log the thought but don't take action await tool_ctx.info("Thinking process recorded") # Return confirmation return "I've recorded your thinking process. You can continue with your next action based on this analysis."
  • Input schema definition for the 'think' tool: 'thought' parameter as an annotated string with description and min_length validation.
    Thought = Annotated[ str, Field( description="The detailed thought process to record", min_length=1, ), ] class ThinkingToolParams(TypedDict): """Parameters for the ThinkingTool. Attributes: thought: The detailed thought process to record """ thought: Thought
  • The register method of ThinkingTool that defines the actual MCP tool handler 'think' using @mcp_server.tool decorator and delegates execution to the call method.
    def register(self, mcp_server: FastMCP) -> None: """Register this thinking tool with the MCP server. Creates a wrapper function with explicitly defined parameters that match the tool's parameter schema and registers it with the MCP server. Args: mcp_server: The FastMCP server instance """ tool_self = self # Create a reference to self for use in the closure @mcp_server.tool(name=self.name, description=self.description) async def think( ctx: MCPContext, thought: Thought, ) -> str: ctx = get_context() return await tool_self.call(ctx, thought=thought)
  • Function that instantiates the ThinkingTool and registers it via ToolRegistry (which invokes the tool's register method).
    def register_thinking_tool( mcp_server: FastMCP, ) -> list[BaseTool]: """Register thinking tools with the MCP server. Args: mcp_server: The FastMCP server instance """ thinking_tool = ThinkingTool() ToolRegistry.register_tool(mcp_server, thinking_tool) return [thinking_tool]
  • Top-level registration call to register_thinking_tool(mcp_server) as part of registering all tools.
    # Initialize and register thinking tool thinking_tool = register_thinking_tool(mcp_server) for tool in thinking_tool: all_tools[tool.name] = tool

Other Tools

Related Tools

  • @hanzoai/mcp
  • @Rai220/think-mcp
  • @flight505/mcp-think-tank
  • @smian0/mcp-agile-flow
  • @cgize/claude-mcp-think-tool
  • @piotrpalek/mcp-thinking-tool

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