blobpedia

list_videos

Browse Celestia-related YouTube videos cached on this server, filtered by channel/date/transcript availability. Celestia-only cache — does NOT search YouTube at large (use a dedicated YouTube tool for that). Metadata only; use get_video for the transcript of one video by id.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No
`since`	No	Earliest published_at (ISO date, e.g. "2026-01-01"). Default: no lower bound.
`offset`	No
`channel`	No	Channel name filter, e.g. "Celestia", "Celestia Foundation", "Modular". Case-insensitive substring.
`has_transcript`	No	If true, only return videos with a stored transcript. If false, only those still missing one. Omit for both.

Schema Changelog

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

First observedJul 20, 2026

TDQS

A4.3/5.0

Behavior4/5

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

No annotations provided, so description carries full burden. It discloses it's a server cache, metadata-only, and doesn't search YouTube. While read-only behavior is implied, explicit 'read-only' would improve. Still, it provides enough behavioral context for safe use.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tightly-coupled sentences: purpose, limitations, and pointer to sibling. No fluff, front-loaded with main action, and every sentence adds value. Excellent structure.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema given, so description should cover return value. It states 'metadata only' but doesn't specify which metadata fields are returned. With 5 parameters and no output schema, this is a notable gap. However, the description is otherwise informative within its scope.

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 60% with descriptions for some parameters. Description adds high-level filter categories (channel, date, transcript) but doesn't detail specific parameter formats or constraints beyond what schema already provides. Adds some context but not substantial new meaning.

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 lists Celestia-related YouTube videos from a cached server, with filters. It uses a specific verb 'Browse' and resource 'YouTube videos cached on this server', distinguishing it from siblings like 'get_video' and general YouTube search tools.

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?

Explicitly states when not to use: 'does NOT search YouTube at large' and directs to 'use a dedicated YouTube tool for that'. Also points to 'get_video' for transcript retrieval, providing clear alternatives.

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

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