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canton-ccpedia

by io.github.UnityNodes

get_validator_fleet

Read-onlyIdempotent

Where do you stand versus other Canton operators on your Splice version? Reports the whole DSO-approved validator fleet as a version distribution; call with no version to see the whole distribution, or pass your own version to get your exact position (early, typical, or dangerously behind most nodes). CCPEDIA-unique: no other public source publishes this. IMPORTANT: versions are self-reported by each operator in its license metadata, not observed, and many reports are months stale; the tool returns how many are fresh so you can qualify the answer. For the pass/fail rule (are you above the required minimum) use get_upgrade_status. Canton ecosystem only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
versionNoYour Splice version, e.g. "0.6.9", to locate it in the distribution.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations declare readOnlyHint, idempotentHint, and non-destructive nature. The description adds critical behavioral context: versions are self-reported, stale, and the tool returns freshness count. This is beyond annotations and fully disclosed.

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?

The description is relatively long but well-structured: purpose first, then usage, then caveats. Every sentence adds unique value, though slightly verbose. Could be slightly trimmed but still effectively front-loaded.

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?

Despite no output schema, the description explains what the tool returns (version distribution, freshness count, position classification). It also specifies ecosystem and caveats, making the output predictable.

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

Parameters5/5

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

The single parameter 'version' has a schema description, but the description adds meaning by explaining its effect (with vs without) and providing an example. Schema coverage is 100%, so the description enhances understanding.

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 clearly states the tool reports the DSO-approved validator fleet version distribution and can show the whole distribution or the user's position relative to other operators. It also distinguishes from the sibling tool get_upgrade_status, making the purpose unambiguous.

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?

Explicit guidance: call with no version for whole distribution, with version for position. It also tells when to use an alternative (get_upgrade_status for pass/fail rules) and restricts to Canton ecosystem. This provides clear when-to-use and when-not-to-use information.

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

All canton-ccpedia toolsInspect
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TDQS

A3.7/5.0
Disambiguation2/5

Many tools have overlapping search/retrieval functionality (search, semantic_search, full_context, search_community, search_github_issues, etc.), and the CIP-specific variants (get_cip, get_cip_history, get_cip_votes, get_cip_mentions, get_cip_citations) are numerous and subtly differentiated. Despite cross-references in the descriptions, the boundaries are fine-grained and an agent is likely to misselect among the 8+ search tools or the 8+ CIP tools.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern (get_x, list_x, search_x, find_x). Mixed styles or camelCase are absent, and the verb choice (get, list, search, find, detect, compare) is semantically appropriate to each action, making the naming highly predictable.

Tool Count1/5

With 88 tools, the surface is extremely overgrown for a single server, far exceeding the 25+ 'too many' threshold and approaching the 50+ 'extreme mismatch' category. Even for a comprehensive ecosystem knowledge base, this creates a massive selection burden and makes the tool set unwieldy for agents.

Completeness5/5

The server covers the full Canton ecosystem: docs, forum, mailing lists, GitHub, CIPs, governance, validators, versions, deprecations, security, and media. There are no glaring gaps in the knowledge domain; every major resource type has retrieval and analysis tools, making the coverage exhaustive with no obvious dead ends.

Resources