Tanod MCP server

utilpeek: generate UUIDs (v4, v7) or ULIDs

generate_ids

Read-only

Create 1–100 random UUID v4, time-ordered UUID v7, or ULID identifiers for unique keys, trace IDs, or sortable records.

Instructions

utilpeek: Generate UUIDs or ULIDs. For numbers, bytes and picks use generate_random. Returns 1-100 new identifiers: random UUID v4, time-ordered UUID v7 (RFC 9562) or ULIDs, optionally strictly increasing within the response (v7 and ULID; per response on purpose, so one caller cannot predict another's next ID). Input: optional kind, version, count and monotonic; an empty body gives one UUID v4. version with kind=ulid, or monotonic with v4, is a 422 (not charged). Typically under 0.1 s. Price: USD 0.001. Free: 10 utilpeek calls per IP per UTC day. Docs: https://tanod.dev/learn/uuid-generator-api.html

Input Schema

TableJSON Schema

Name	Required	Description	Default
`kind`	No	uuid (default) or ulid.	uuid
`count`	No	How many (1-100, default 1).
`version`	No	UUID version 4 (random, default) or 7 (time-ordered); kind=uuid only.
`monotonic`	No	v7 / ULID only: strictly increasing within this response.

Output Schema

TableJSON Schema

Name	Required	Description
`ids`	No
`kind`	No
`count`	No
`error`	No	Only on an error result: an object {code, message}, or the reason string of an x402 PaymentRequired object.
`version`	No
`monotonic`	No
`generated_at`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.3.0Oct 15, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Annotations already declare readOnly/destructive/idempotent hints, yet the description adds substantial context: monotonicity applies per-response deliberately so callers cannot predict other callers' IDs, invalid combos return 422 uncharged, latency is typically under 0.1s, and pricing/free-tier limits are given.

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?

Front-loaded with the core action and the sibling alternative, then defaults, error cases, latency, and pricing. Every clause is useful, though pricing/free-tier/docs appended to the same paragraph makes it slightly dense.

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?

An output schema exists so return values need no explanation; the description still covers input defaults, valid combinations, failure modes, timing, and cost. Nothing needed to invoke it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds cross-parameter semantics the schema does not encode: `version` is only valid with kind=uuid and `monotonic` only with v7/ULID, both a 422. That is genuine meaning beyond the per-field descriptions.

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 (Generate) and resource (UUIDs v4/v7, ULIDs) and explicitly routes the agent away from the sibling generate_random. An agent can pick this over generate_random without opening either schema.

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?

Gives the exclusion rule ('For numbers, bytes and picks use generate_random') and the default behavior ('an empty body gives one UUID v4'). It also states which combinations are rejected (version with kind=ulid, monotonic with v4), leaving little to infer.

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

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