Timeline of what changed on Celestia recently across blobpedia (new/changed CIPs, forum threads, blog posts, GitHub releases, radar alerts), newest first. Celestia activity only — not a GitHub commit feed (use a GitHub tool) and not general crypto news (use a web-search tool). Use get_trending for what is popular rather than what is new.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | ||
| limit | No |
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?
No annotations are provided, so the description carries the full burden. It clearly states the return is a timeline of what changed, which is a read operation, but it does not explicitly disclose that it has no side effects, no permission requirements, or any pagination/rate-limit behavior. The description is adequate for understanding the operation, but lacks the behavioral detail that would be ideal for a tool with zero annotation coverage.
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?
Three sentences with zero waste. The primary purpose is stated first, then the scope limitation, then routing to alternatives. Every sentence earns its place and the information is front-loaded. This is a model of concise, structured description.
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 only two parameters, no required parameters, and no output schema, the description gives a good sense of the return type and scope. However, the absence of any mention of the parameters' semantics is a notable gap – an agent must infer what 'days' and 'limit' actually do. The overall picture is fairly complete for a read-only timeline tool, but the parameter documentation gap prevents a higher score.
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?
Schema description coverage is 0%, yet the description does not explain either the 'days' or 'limit' parameter. The defaults (7 and 50) are in the schema but the meaning – that days is the lookback window and limit is the max number of results – is not communicated in the description. An agent can guess from the names, but the tool should explicitly document these semantics since the schema itself has no descriptions.
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?
The description clearly specifies the verb (get), the resource (recent changes across blobpedia), and the exact content scope (CIPs, forum threads, blog posts, GitHub releases, radar alerts). It goes beyond a generic statement by naming the sources and the ordering (newest first), and it differentiates from sibling tools like get_trending and GitHub-specific tools.
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?
The description provides explicit usage guidance: it tells agents that this tool is for Celestia activity only, explicitly not GitHub commit feeds or general crypto news, and names the alternative tool (get_trending) for popularity-based queries. This is strong routing guidance that leaves nothing to inference.
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.