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export_projects

Read-only

Export Gryzzly project data as CSV or XLSX. The endpoint requires a browser session, so using an API key often fails with an error instead of a file.

Instructions

Download Gryzzly's project export, as CSV or XLSX. Upstream this endpoint wants a browser session, so with an API key it usually fails with an explanation rather than a file.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoLast day of the period.
fromNoFirst day of the period.
formatNoThe file format. Defaults to `csv`.
save_toNoA path on the machine running this server to write the file to.
projectsNoThe projects to export, by name, code or id.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNoSet when the file was too large to inline.
textNoThe file itself, when it is text and small enough to read here.
bytesYesHow many bytes came back.
saved_toNoWhere the file was written, when `save_to` was given.
content_typeYesThe file's media type, as Gryzzly labelled it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint, openWorldHint), and the description adds real value beyond them by disclosing the upstream browser-session dependency and the typical API-key failure mode. It does not mention the disk side effect implied by `save_to`, which is the one behavior left dark.

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 sentences, no filler, and the most decision-relevant fact (it often fails without a browser session) is stated up front rather than buried. Every sentence 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?

An output schema exists, so return-value explanation is unnecessary, and the description covers the critical failure mode. The remaining gap is what happens when `projects` is left null (all projects?) and the fact that `save_to` writes to the server's filesystem.

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 description coverage is 100%, so every parameter (including the format enum and the date bounds) is already documented in the schema. The description only echoes the CSV/XLSX formats, adding no syntax or default detail beyond what the schema provides — baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Download Gryzzly's project export") and names the output formats (CSV or XLSX), so the agent knows this produces a file rather than records. It doesn't explicitly contrast with the sibling export_times_and_leaves, but the resource name is specific enough to separate the two.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The caveat that the endpoint "usually fails with an explanation rather than a file" when using an API key is a genuinely useful signal about when this tool will and won't succeed. However, no alternatives are named (e.g. list_projects for querying data), and there's no guidance on defaults such as what happens when `projects` is omitted.

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