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Riveter MCP Server

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Read-onlyIdempotent

Read Riveter reference topics such as output schemas, limits, webhooks, and errors before configuring columns or troubleshooting API limit messages.

Instructions

Reference docs for using Riveter well. Call before writing an output column spec or when an error mentions a limit. Topics: overview, enrich_modes, column_config, run_when, formats, tools, examples, credits, datasets_vs_enrichment, datasets, pinned_columns, output_schema, limits, webhooks, monitors, errors.

Input Schema

NameRequiredDescriptionDefault
topicYesWhich topic to read

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.5

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, closed-world, non-destructive, so the safety profile is fully covered. The description adds only that this returns static reference text keyed by topic, and does not mention response format (markdown vs plain text) or size. Useful but modest value beyond structured data.

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?

Two short sentences front-load purpose and the primary trigger, then list topics. The topic enumeration duplicates the enum verbatim and costs space, but it aids scanning and is not harmful.

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?

Single required parameter, no output schema, fully described enum; the description supplies the situational triggers the schema cannot. It could close the loop by stating what the docs return, but nothing essential for correct invocation is missing.

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 100% and the `topic` enum lists all 16 values with a description ('Which topic to read'). The description re-lists the same topics and adds no semantics about how to choose between overlapping topics (e.g., datasets vs datasets_vs_enrichment). Baseline 3 is appropriate when the schema does the work.

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+resource ('Reference docs') scoped to the Riveter product and enumerates the available topics, which makes it unmistakable against siblings like list_tools or get_account. 'Using Riveter well' is slightly marketing-ish phrasing, but the topic list grounds the purpose concretely.

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?

Gives two concrete call triggers: before authoring an `output` column spec, and when an error mentions a limit. That is real when-to-use guidance rather than implied context. It doesn't say when the tool is unnecessary (e.g., for run status, use get_run), so it stops short of full routing guidance.

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