ask_pipeworx_grounded
ActiveTool of mcp-pubmed
Hallucination-resistant answer mode for high-stakes reads. Same routing as ask_pipeworx — picks the right tool from 4,679 across 1213 sources, fills arguments, fetches the data — then EXTRACTS the answer using ONLY what the tool result contains. Returns {answer, evidence (verbatim quote), confidence, source, fetched_at, refusal_reason:null} on success, OR an explicit refusal {answer:null, refusal_reason:"not_in_source"|"no_tool_match"|"tool_error"|"data_truncated"|"llm_error"} when the data doesn't directly answer. Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts (financial verdicts, legal claims, medical lookups, public statements). Costs one extra LLM call vs ask_pipeworx — prefer ask_pipeworx for casual lookups.
Parameters schema
{
"type": "object",
"required": [
"question"
],
"properties": {
"q": {
"type": "string",
"description": "Alias for question."
},
"text": {
"type": "string",
"description": "Alias for question."
},
"input": {
"type": "string",
"description": "Alias for question."
},
"query": {
"type": "string",
"description": "Alias for question."
},
"prompt": {
"type": "string",
"description": "Alias for question."
},
"question": {
"type": "string",
"description": "Your question in natural language. Accepts query, q, prompt, text, input as aliases."
}
}
}Parent server
mcp-pubmed
https://github.com/pipeworx-io/mcp-pubmed
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