search_postsFull-text search over recent posts from catalogued channels (1k+ view posts). Returns text snippets, channel and view counts.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results (default 10) | |
| query | Yes | Search query |
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 carries the transparency burden. It discloses the operation type (full-text search, implying read-only), the scope limitation (catalogued channels, 1k+ view posts), and what is returned. It does not mention ordering or pagination, but for a search tool this is acceptable.
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?
The description is a single sentence, front-loaded with the core functionality, followed by a succinct mention of return values. No redundant information or filler.
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 simple tool with two parameters and no output schema, the description adequately covers the necessary context: what the tool searches, the constraints (catalogued, 1k+ views, recent), and what the response includes. No critical information is missing.
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 input schema has 100% description coverage for both parameters. The description adds no additional meaning beyond the schema; it does not explain query syntax or limit behavior. The baseline of 3 applies because the schema does the heavy lifting.
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 states a specific action ('Full-text search') on a specific resource ('recent posts from catalogued channels (1k+ view posts)') and lists return items ('text snippets, channel and view counts'). It distinguishes from siblings like 'search_telegram' by narrowing to channel posts with a view threshold.
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 clear context for when to use this tool: searching recent posts from catalogued channels with at least 1k views. It does not explicitly mention alternatives or exclusions, but the scope is well-defined enough to infer appropriate usage relative to sibling tools.
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.
Each tool targets a distinct data need: ranked channel discovery, exact channel lookup, marketplace listings, marketplace stats, post-content search, and catalog entity search. Even the two search tools are clearly separated by whether they search post content or Telegram catalog entries.
Names are readable and consistently snake_case, but they mix verb-led names like search_posts and search_telegram with noun-led names like channel_stats, market_listings, market_stats, and best_channels_by_category. The market_* and search_* pairs are helpful, but there is no uniform verb_noun pattern across the set.
Six tools is a well-scoped size for a Telegram catalog and search server. Each tool earns its place by covering channel discovery, channel lookup, post search, and marketplace data without redundancy.
The read-only surface is largely complete: search, top channels, exact stats, and marketplace stats/listings are all covered. A direct way to retrieve recent posts for a specific channel or enumerate all categories would close the remaining minor gaps.