Skip to main content
Glama
GlaserIngo

Stript MCP Bridge

by GlaserIngo

Fetch a Stript anonymization result

stript_fetch_result
Read-only

Fetch anonymized Stript document results, waiting if the document is still in review. Returns only anonymized content, never original text.

Instructions

Use this to fetch the anonymized result of a Stript document, for example after a pending_review status or after the app was restarted mid-review. If the document is still in review, this call WAITS for the user to finish the review in Stript and returns the result as soon as they click Anonymize. When it returns pending_review instead, call it again immediately to keep waiting, and repeat while the result says pending_review and the user has not cancelled. The document_id is optional, without it the most recent document in the project is fetched, so a plain "fetch my Stript result" works. Returns only anonymized content, never the original document text. Reading a stored result is free, it never consumes an evaluation document.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
document_idNoThe Stript document id to fetch. Omit for the most recent document.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
nextNo
typesNo
statusYes
warningsNo
evaluationNo
project_idNo
document_idNo
output_fileNo
replacementsNo
residual_riskNo
anonymized_textNo
degraded_reasonsNo
detections_totalNo
reduced_accuracyNo
Behavior5/5

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

The description discloses important blocking behavior ('this call WAITS for the user to finish the review'), the pending_review return/retry pattern, and resource implications ('Reading a stored result is free, it never consumes an evaluation document'). It also states that only anonymized content is returned, never original text. These go well beyond the readOnlyHint/destructiveHint annotations.

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?

Though the description is longer than typical, every sentence adds a distinct piece of information: trigger conditions, blocking behavior, retry instructions, optional parameter semantics, output guarantee, and cost implication. It is front-loaded with the core action and remains tightly structured.

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?

Given the tool's wait-and-retry behavior and optional parameter, the description covers the full invocation loop, the output constraint, and the resource impact. Combined with the output schema, this is sufficiently complete for an agent to use the tool correctly without additional context.

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 schema already fully describes document_id as optional and says 'Omit for the most recent document.' The description repeats the same information in natural language ('without it the most recent document in the project is fetched') and adds a friendly paraphrase, but no new semantic meaning beyond the schema. With 100% schema coverage, the baseline of 3 is 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 the specific verb+resource: 'fetch the anonymized result of a Stript document,' clearly distinguishing it from siblings like stript_anonymize_file (anonymize) and stript_restore (restore). It adds context about pending_review and app restarts, making the purpose precise.

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?

It explicitly states when to use: 'after a pending_review status or after the app was restarted mid-review,' and gives a concrete retry loop: 'call it again immediately to keep waiting, and repeat while the result says pending_review.' It also explains the optional parameter use case, so an agent knows a bare call works.

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/GlaserIngo/stript-mcp'

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