Skip to main content
Glama

canton-ccpedia

by io.github.UnityNodes

get_validator

Read-onlyIdempotent

Look up an individual Canton validator node in the DSO registry by name or party id: its sponsor, self-reported Splice version and how stale that report is, when it was last active, the round range it has been earning over, and how many reward coupons it has missed. CCPEDIA-unique: derived from the DSO validator licenses on the public Scan API. Use for "is node X still live", "how reliable is X", and "who onboarded X" where the registry records a distinct sponsor (about half the fleet does; the rest name themselves and this says so rather than repeating the node name back). For the version distribution across the whole fleet use get_validator_fleet; for whether a version passes the MainNet minimum use get_upgrade_status; for Super Validator GOVERNANCE voting records use list_votes_by_sv, which is a different population. Canton ecosystem only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesValidator name or party id, whole or partial, e.g. "GSF-validator-2" or "MPCH".
limitNoMaximum matches to return (default 10, max 50).

Schema Changelog

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

  1. Changed2 schema fields changed
    • changedInput schema / properties / limit / maximum
      Previous value: -9007199254740991New value: +50
    • changedInput schema / properties / limit / minimum
      Previous value: --9007199254740991New value: +1
  2. Added

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare the tool read-only, idempotent, and non-destructive. The description adds meaningful behavioral context: data derives from the DSO validator licenses on the public Scan API, the version is self-reported with staleness indication, and the sponsor caveat that about half the fleet self-names rather than having a distinct sponsor. No contradictions with annotations.

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 dense and information-rich, with every sentence contributing value (source, use cases, exclusions, caveats). It is somewhat lengthy with parenthetical asides, but well-structured and front-loaded with the core purpose.

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 having no output schema, the description explicitly enumerates all returned fields: sponsor, Splice version, staleness, last active, round range, and missed coupons. It also covers source, scope limitation ('Canton ecosystem only'), and cross-references to related tools, making it fully self-contained for an agent to understand behavior and output.

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%, with both parameters (name and limit) fully documented including examples, constraints, and defaults. The description restates 'name or party id' but does not add significant semantic value beyond the schema. Therefore baseline 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 clearly identifies the tool as a lookup for an individual Canton validator node in the DSO registry by name or party id, and lists the specific data returned. It explicitly distinguishes itself from sibling tools like get_validator_fleet, get_upgrade_status, and list_votes_by_sv, 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?

The description provides explicit use cases ('is node X still live', 'how reliable is X', 'who onboarded X') and directly names alternatives for different needs (fleet version distribution uses get_validator_fleet, version minimum uses get_upgrade_status, SV governance uses list_votes_by_sv). This gives clear when-to-use and when-not-to-use guidance.

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
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

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