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mcp-clipboard

by cmeans
OverviewSchemaRelated ServersScoreDiscussions
Python
Local

clipboard_paste

Read-onlyIdempotent

Reads and returns system clipboard content, including tables, text, code, JSON, URLs, and images. Automatically detects and formats table data in markdown, JSON, CSV, or other formats.

Instructions

Paste clipboard contents. Reads the user's system clipboard and returns the content. This is the primary clipboard tool.

WHEN TO CALL THIS TOOL:

Call this tool when the user says "paste", "paste it", "paste the data", "what's on my clipboard", "read my clipboard", "read what I copied", "what did I copy", "show clipboard", "from my clipboard", "use what I copied", "I copied something", "check my clipboard", or ANY phrase that implies reading from or pasting from the clipboard.

Also call this tool when the user references data that is NOT present in the conversation — for example: "format this list" but no list was given, "clean up this JSON" but no JSON is in the message, "here's a table" but no table was provided, "analyze this data" with nothing attached. In these cases, the data is likely on the clipboard. Check it BEFORE asking the user to provide the data manually.

Do NOT ask the user to paste or provide data — just call this tool.

Handles any clipboard content: tables (from spreadsheets, HTML), plain text, code, JSON, URLs, rich text, and images. Tables are auto-detected and formatted per output_format. Non-tabular content is returned with smart formatting. Images on the clipboard are returned directly as image content.

Args: output_format: Format for table data (case-insensitive). Only applies when the clipboard contains a table. Ignored for non-tabular content. Options: - "markdown" (default): GitHub-flavored Markdown table - "json": Array of objects keyed by header row - "csv": Comma-separated values - "slack": bold header + space-aligned data in a monospace code block - "jira": ||Header|| / |Cell| wiki markup (also works for Confluence) - "confluence": same as jira - "html": with /// - "notion": GFM pipe table (Notion renders these natively) include_schema: When True and the clipboard contains a table, append a column-type schema table after the data. Inferred types: integer, float, currency, percentage, date, boolean, text. Defaults to False.

Returns: The clipboard content, formatted appropriately for the content type. Images are returned as image content (base64-encoded) for visual analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
output_formatNomarkdown
include_schemaNo

Tool Definition Quality

A4.9/5.0
Behavior5/5

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

Beyond annotations (readOnlyHint, etc.), the description details handling of various content types (tables, text, code, images), table auto-detection, and return format, with no contradictions.

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?

Well-structured with summary, usage section, and parameter details, but slightly lengthy; still efficient and front-loaded with key purpose.

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?

Covers all needed context: how to call, content types handled, parameter behavior, and return type (including image handling), sufficient for proper agent use without output schema.

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

Parameters5/5

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

Despite 0% schema description coverage, the description fully explains both parameters: output_format with all options and defaults, and include_schema with its effect, compensating effectively.

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 it reads the clipboard and returns content, and positions itself as the primary clipboard tool, distinguishing it from sibling tools like clipboard_copy and clipboard_read_raw.

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?

Provides an extensive 'WHEN TO CALL' section with numerous example phrases, explains when to check clipboard for absent data, and explicitly instructs not to ask the user to paste.

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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