Search across release-notes bodies of all indexed Celestia repos for a feature/keyword. Celestia-specific. Use to find which release first mentioned X.
| Name | Required | Description | Default |
|---|---|---|---|
| feature | Yes | Feature keyword, e.g. "blob size limit", "namespace", "data availability sampling". |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry behavioral disclosure. It communicates a read-only search across all indexed Celestia repos and implies release-level results, but it does not describe matching semantics, result structure, ordering, or potential limitations. This is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, each earning its place: the first states the action and scope, the second states the intended use case. No filler or redundant details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one simple, fully documented parameter, the description covers scope and purpose well. However, since there is no output schema, a bit more detail about what the returned results look like would make it fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'feature' is fully described in the schema with examples. The description adds only the phrase 'feature/keyword', which aligns with the schema but does not provide additional semantic value beyond what the schema already offers.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description names a specific action ('Search'), a specific resource ('release-notes bodies of all indexed Celestia repos'), and a clear intent ('find which release first mentioned X'). This distinguishes it from generic siblings like search and semantic_search by scope and domain.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides a clear use case: use when you need to know which release first mentioned a feature or keyword. It does not explicitly list exclusions or alternative sibling tools, but the context is sufficient for most agents.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.