Skip to main content
Glama

upload_attachment

Attach a local file to a Plane task. Uploads the file to S3 using a presigned URL and confirms the attachment.

Instructions

Attach a file from disk to a task.

Three-step flow under the hood: request presigned S3 URL from Plane, upload the bytes directly to S3, confirm upload back to Plane. Returns the created attachment metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoDisplay filename in Plane. Defaults to the basename of file_path.
issue_idYesTask UUID to attach the file to.
file_pathYesAbsolute or CWD-relative path to a local file on the MCP server's filesystem (same machine as the agent).
mime_typeNoMIME type override. If omitted, auto-detected from the file extension.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description carries the full transparency burden. It discloses the three-step S3 presigned URL flow, direct byte upload, and confirmation, plus the fact that it returns created attachment metadata. This goes beyond a trivial 'uploads a file' statement, although it omits potential failure modes or size limits.

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 only two sentences: the first is a front-loaded, clear statement of purpose, and the second packs the multi-step mechanics into a compact, readable sentence. Every word earns its place.

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 rich input schema (100% coverage) and the presence of an output schema, the description sufficiently explains the tool's behavior and return value. The only minor gap is the absence of mention of prerequisites or error conditions, but for a file-upload tool with this schema, the description is complete enough.

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?

The input schema has 100% description coverage, so the schema already documents all four parameters clearly. The description adds no additional parameter-level detail beyond what the schema provides, making the baseline score of 3 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 opens with 'Attach a file from disk to a task,' which clearly states the specific action and resource. It further distinguishes itself from sibling read/delete tools like get_attachment_url and delete_attachment by describing the upload flow and return value.

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 opening sentence clearly indicates when to use this tool: to attach a local file to a task. It provides clear context without explicit exclusions or alternative tool names, though it does not mention related alternatives like add_comment_with_image.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/babazulu/plane-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server