User Posts
| Name | Required | Description | Default |
|---|---|---|---|
| trim | No | Set to true for a trimmed down version of the response | |
| handle | No | Truth Social username | |
| user_id | No | Truth Social user id. Use this for faster response times. Trumps is 107780257626128497. It is the 'id' field in the profile endpoint. | |
| next_max_id | No | Used to paginate to next page |
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 full responsibility for disclosing behavior. 'User Posts' provides no information about read-only vs. mutating behavior, pagination via next_max_id, response shape, rate limits, or other operational traits. The description is essentially empty of behavioral content.
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?
While extremely short ('User Posts'), this is under-specification rather than effective conciseness. It lacks any structuring or front-loaded actionable information. The brevity does not serve the agent's ability to understand or invoke the tool.
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?
The tool has 4 parameters, no output schema, and many similar sibling tools, yet the description provides zero contextual information. It does not explain what data is returned, how to paginate, or how this differs from related tools. The description is completely inadequate for the tool's complexity.
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 100%, so the baseline is 3. The parameters (trim, handle, user_id, next_max_id) are fully described in the schema, including helper hints like Trump's user_id and the purpose of next_max_id. The description adds no additional parameter semantics but does not need to, given the schema's completeness.
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 'User Posts' is a noun phrase that merely restates the tool name. It does not specify an action (e.g., retrieve, scrape, list) or resource scope, and it fails to distinguish this tool from many similar siblings like scrapecreators_posts, scrapecreators_profile_posts, and scrapecreators_user_tweets.
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?
No guidance is provided on when to use this tool versus alternative siblings. The description lacks any context about use cases, prerequisites (e.g., handle or user_id), or scenarios where another tool would be more appropriate.
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.
The tool set has significant overlap and ambiguity, particularly within the 'scrapecreators_' prefix where many tools appear to target similar social media platforms and content types (e.g., 'scrapecreators_posts', 'scrapecreators_posts_get', 'scrapecreators_post', 'scrapecreators_post_get'). Additionally, tools like 'tavily_research' and 'tavily_search' have overlapping purposes with 'web_search_exa', making it difficult for an agent to distinguish when to use each. While some tools like 'get_credits' or 'ideogram_v3' are distinct, the overall set is confusing due to redundant functionalities.
Naming conventions are highly inconsistent across the tool set. There is a mix of snake_case (e.g., 'get_credits'), kebab-case (e.g., 'find-hooks'), and verbose prefixes (e.g., 'scrapecreators_'). The 'scrapecreators_' tools themselves vary in structure, with some using underscores and others not, and there are duplicate names with slight variations (e.g., 'scrapecreators_ad_details' vs. 'scrapecreators_ad_details_get'). This lack of a predictable pattern makes the tool set chaotic and hard to navigate.
With 124 tools, the count is extremely high and inappropriate for the server's purpose, which appears to be marketing and social media data collection. This many tools suggests poor scoping, likely due to redundancy (e.g., multiple scraping tools for similar platforms) and overlapping functionalities. A well-scoped server in this domain should have far fewer tools, typically in the range of 10-30, to avoid overwhelming agents and ensure clarity.
Despite the high tool count and redundancy, the server covers a broad range of marketing-related functions comprehensively. It includes tools for social media hooks, content validation, SEO analysis (e.g., backlinks, keywords), voice archetypes, copywriting frameworks, and extensive scraping across multiple platforms. There are no obvious major gaps for the marketing domain, as it supports data gathering, content creation, and analysis across various networks and metrics, allowing agents to perform core marketing workflows effectively.