get_threadFetch a post thread by URI. Returns the parent post and all replies in conversation order with timestamps, authors, and engagement data.
| Name | Required | Description | Default |
|---|---|---|---|
| post_uri | Yes | AT URI of the post (at://did/app.bsky.feed.post/rkey) |
| Name | Required | Description | Default |
|---|---|---|---|
| post | Yes | The parent post | |
| replies | Yes | Reply posts in conversation order |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "post": {
+ "description": "The parent post",
+ "properties": {
+ "author": {
+ "description": "Author's display name or handle",
+ "type": "string"
+ },
+ "createdAt": {
+ "description": "ISO timestamp of post creation",
+ "type": "string"
+ },
+ "handle": {
+ "description": "Author's handle",
+ "type": "string"
+ },
+ "likes": {
+ "description": "Number of likes",
+ "type": "number"
+ },
+ "replies": {
+ "description": "Number of replies",
+ "type": "number"
+ },
+ "reposts": {
+ "description": "Number of reposts",
+ "type": "number"
+ },
+ "text": {
+ "description": "Post content text",
+ "type": "string"
+ },
+ "uri": {
+ "description": "AT URI of the post",
+ "type": "string"
+ }
+ },
+ "required": [
+ "uri",
+ "author",
+ "handle",
+ "text",
+ "createdAt",
+ "likes",
+ "reposts",
+ "replies"
+ ],
+ "type": "object"
+ },
+ "replies": {
+ "description": "Reply posts in conversation order",
+ "items": {
+ "properties": {
+ "author": {
+ "description": "Author's display name or handle",
+ "type": "string"
+ },
+ "createdAt": {
+ "description": "ISO timestamp of post creation",
+ "type": "string"
+ },
+ "handle": {
+ "description": "Author's handle",
+ "type": "string"
+ },
+ "likes": {
+ "description": "Number of likes",
+ "type": "number"
+ },
+ "replies": {
+ "description": "Number of replies",
+ "type": "number"
+ },
+ "reposts": {
+ "description": "Number of reposts",
+ "type": "number"
+ },
+ "text": {
+ "description": "Post content text",
+ "type": "string"
+ },
+ "uri": {
+ "description": "AT URI of the post",
+ "type": "string"
+ }
+ },
+ "required": [
+ "uri",
+ "author",
+ "handle",
+ "text",
+ "createdAt",
+ "likes",
+ "reposts",
+ "replies"
+ ],
+ "type": "object"
+ },
+ "type": "array"
+ }
+ },
+ "required": [
+ "post",
+ "replies"
+ ],
+ "type": "object"
+}Input schema / examplesAdded value: +[
+ {
+ "post_uri": "at://did:plc:ewvcqgxlrk52n5jevxgs3ybu/app.bsky.feed.post/3k7f4x2z9w1a5m3"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive. The description adds value by disclosing the return structure: parent post + replies in conversation order with timestamps, authors, and engagement data. This goes beyond the annotations, providing useful behavioral context.
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 well-structured sentence that front-loads the action and resource, then lists the return contents. Every word earns its place with no redundancy 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?
With only one parameter, an output schema, and annotations covering safety, the description is fully complete. It even goes beyond requirements by explaining the return payload (timestamps, authors, engagement data), making the tool's behavior clear.
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 coverage is 100% (post_uri is fully described with example and format). The description does not add any additional parameter information beyond the schema, so the baseline score of 3 is appropriate. No gap to compensate.
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 clearly states 'Fetch a post thread by URI' with a specific verb and resource, and distinguishes itself from sibling tools like get_posts by focusing on thread structure (parent + replies). The return content is explicitly listed.
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 implies usage context (fetching a thread by URI) but does not explicitly state when to use this tool over alternatives like get_posts or search_posts. No exclusions or alternative references are provided, so the guidance is implicit rather than explicit.
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 have clearly distinct roles, but several overlapping pairs create ambiguity: ask_pipeworx vs ask_pipeworx_beta are explicitly identical today, discover_tools vs suggest_questions both serve discovery/onboarding, and bet_research vs polymarket_edges both address betting-edge questions. The detailed descriptions help, but an agent could still select the wrong tool in these cases.
The set uses at least four naming conventions: get_* for Bluesky reads, verb_noun for Pipeworx tools (ask_pipeworx, resolve_entity, validate_claim), polymarket_* prefixed tools, and verb-only memory tools (remember, recall, forget). Each subgroup is internally consistent, but the overall mix feels inconsistent and unpredictable.
39 tools is well beyond the typical well-scoped server, and the scope sprawls across Bluesky reads, Pipeworx data, Polymarket analysis, memory, subscriptions, and one-off utilities like generate_llms_txt and scan_dependency. The count would be more reasonable split into separate servers; as-is it feels heavy and unfocused.
Within the server's evident scope, coverage is strong: Bluesky read operations, Pipeworx query/research/verification, entity profiling, and subscription lifecycle are all represented. The main gaps are write actions for Bluesky (posting, following, liking) and a few auxiliary features that are only partially integrated, but no critical workflow dead-ends appear for the primary data-research use cases.