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debanshd

Tavily Web Search MCP Server

by debanshd

read_clipboard

Retrieve text from your macOS clipboard to use as search queries for web research through the Tavily Web Search MCP Server.

Instructions

Read and return the current clipboard text (macOS). Uses pbpaste.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • server.py:65-77 (handler)
    The core handler function for the 'read_clipboard' MCP tool. Decorated with @mcp.tool(), which handles both implementation and registration. Uses subprocess to call 'pbpaste' for reading macOS clipboard content.
    @mcp.tool()
    def read_clipboard() -> str:
        """Read and return the current clipboard text (macOS). Uses `pbpaste`."""
        try:
            completed = subprocess.run([
                "pbpaste"
            ], check=False, capture_output=True, text=True)
            if completed.returncode != 0:
                return f"❌ Failed to read clipboard (pbpaste exited {completed.returncode})."
            return (completed.stdout or "").strip()
        except Exception as e:
            return f"❌ Error reading clipboard: {str(e)}"
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses the tool reads clipboard text using `pbpaste` on macOS, which implies platform dependency and read-only behavior. However, it lacks details on error handling, permissions needed, or what happens if clipboard is empty, leaving behavioral gaps.

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 extremely concise with two sentences that efficiently convey purpose, platform, and implementation. Every word adds value, and it is front-loaded with the core action, making it highly efficient and well-structured.

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?

Given the tool's simplicity (0 parameters, no annotations, but has an output schema), the description is mostly complete. It covers the action, resource, and platform, but could benefit from mentioning the output format or handling edge cases, though the output schema may mitigate this.

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 tool has 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description does not add parameter semantics, but this is appropriate given the lack of parameters, warranting a baseline score above 3 for adequate handling.

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 specific action ('Read and return') and resource ('current clipboard text'), with platform specificity ('macOS') and implementation detail ('Uses `pbpaste`'). It distinguishes from sibling 'write_clipboard' by being the read counterpart.

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 implies usage context by specifying 'macOS' and the clipboard resource, but does not explicitly state when to use this tool versus alternatives like 'write_clipboard' or other data retrieval methods. It provides clear context but lacks explicit exclusions or alternatives.

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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