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Glama

blobpedia

by io.github.UnityNodes

get_foundation_info

Who runs Celestia: leadership and team members of the Celestia Foundation and Celestia Labs — names, roles and background — plus the headline figures from the official celestia.org About page. Use for "who is the CEO/CTO", "who works on Celestia", or team-background questions. People and org facts only — this is NOT Celestia documentation (use search or get_doc), NOT CIPs or their discussion (use list_cips/get_cip and get_cip_mentions), and it holds no grant-programme, board-seat or membership records.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
topicYesFree-text topic, e.g. "team", "executive director", "working groups", "membership", "grants", "board".

Schema Changelog

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

  1. First observed

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It does not mention side effects, authorization, or data freshness, but it does clarify the tool's scope (people and org facts only), which adds some transparency. For a simple read-only tool, this is adequate but not comprehensive.

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 a single paragraph that efficiently covers purpose, examples, and exclusions. It is well-structured and informative without being verbose. Minor improvement could be to separate usage guidelines more clearly.

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?

Given the tool's simplicity, no output schema, and moderate schema coverage, the description provides a good overview of what is included and excluded. However, it does not describe the output format, which would help an agent interpret results. Overall, it is largely complete for decision-making.

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

Parameters2/5

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

Schema coverage is 50% (only 'topic' has a description; 'limit' lacks one). The description does not elaborate on parameters or their usage beyond the schema. For a tool with two parameters and low schema coverage, the description should compensate but does not, making parameter understanding reliant solely on schema.

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 provides info on who runs Celestia, including leadership, team members, roles, background, and headline figures. It explicitly distinguishes itself from other tools by listing what it does NOT cover (documentation, CIPs, etc.), which is strong differentiation.

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 usage examples (e.g., 'who is the CEO/CTO') and explicit when-not-to-use conditions with references to alternative tools (e.g., use search or get_doc for documentation). This fully satisfies the guideline dimension.

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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TDQS

A3.9/5.0
Disambiguation4/5

Most tools target clearly distinct content types and actions, and descriptions carefully carve out boundaries (e.g. get_network_state vs get_network_stats, get_discussion vs get_github_discussion). However, the overlapping get_/find_/search_ families plus the very similar network_state/network_stats names leave some edge cases where an agent could select the wrong tool.

Naming Consistency4/5

The dominant convention is verb_noun (find_*, get_*, list_*, search_*), and get/list/find roughly map to id-based retrieval, browsing, and discovery. Deviations like learning_path, ecosystem_dependency_graph, and semantic_search break the pattern, and the get_ vs find_ vs search_ boundaries are not perfectly predictable.

Tool Count2/5

43 tools is on the high side for a single MCP server; even though the Celestia knowledge domain is broad, the surface is heavy and will increase selection cost. Most tools are individually useful, but the set would benefit from consolidation, e.g. merging release tools or search variants.

Completeness4/5

The server covers an unusually broad range of content types—CIPs, docs, forum, GitHub issues/discussions, releases, videos, whitepapers, ecosystem, and network state—with list/get/search access for most. Minor gaps remain, such as no dedicated blog retrieval and get_issue_status only returning status rather than full issue body, but core knowledge workflows have no dead ends.

Resources