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colab_upload

Upload a local file from the working directory to a Colab VM, e.g. remote_path '/content/data.csv'. Use it for small files; download large datasets on the VM instead.

Instructions

Upload one local file (inside the working directory) to the VM, e.g. remote_path '/content/data.csv'. Limited by COLAB_MCP_MAX_UPLOAD_MB (default 100): for big data, download it on the VM instead (colab_exec / colab_job_start).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sessionNo
local_pathYes
remote_pathYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full burden, and it does disclose a real constraint: the COLAB_MCP_MAX_UPLOAD_MB limit (default 100MB) and the working-directory restriction. It omits overwrite behavior, authentication, and transfer-failure semantics, but the size-limit disclosure is genuinely useful context.

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?

Two tight sentences: the core action and example come first, the caveat and alternative routing second. No wasted phrasing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be explained. However, for a 3-parameter tool with zero schema description coverage, the description leaves 'session' entirely undocumented and gives no explicit path-format guidance for local_path.

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?

Schema coverage is 0%, so the description must compensate. It clarifies remote_path with a concrete example ('/content/data.csv') and implies local_path is relative to the working directory, but the 'session' parameter is never mentioned and local_path format is left to inference.

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?

States a specific verb (upload), a precise resource (one local file inside the working directory), and the destination (the VM). The word 'one' implicitly distinguishes it from the colab_upload_dir sibling, and the remote_path example makes the resource concrete.

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?

Explicitly routes large-data cases away from this tool, naming the alternatives (colab_exec / colab_job_start) and the trigger (COLAB_MCP_MAX_UPLOAD_MB limit). It does not explicitly state how this differs from colab_upload_dir for multi-file cases, so the sibling routing is only implied.

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