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Healthdata

by io.github.pipeworx-io

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Idempotent

Create a proactive monitoring subscription to a live-data event stream. Returns the new subscription id. Requires a Pipeworx OAuth account (anonymous + BYO cannot persist subscriptions). Supported types: "sec_8k" (8-K filings matching ticker + item codes — e.g. items:["5.02"] = officer change), "polymarket_edge" (Polymarket↔Kalshi cross-venue mispricings — params:{topic:"fed"}), "fred_series" (new FRED observations — params:{series_id:"UNRATE"}). Delivery channels: feed (always on — pull via recent_alerts or GET registry.pipeworx.io/alerts.json), and optionally email (set delivery:{email:"you@x.com"}) or sms (delivery:{sms:"+15551234567"} — phone must be verified at /account first; 10/day cap).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesSubscription type.
paramsYesType-specific filter. sec_8k: {ticker:"AAPL", items?:["5.02","1.01"]}. polymarket_edge: {topic:"fed", min_spread_bps?:500}. fred_series: {series_id:"UNRATE"}. patent_grant: {applicant:"Apple Inc."}. clinical_trial: {sponsor?:"Pfizer", condition?:"lung cancer", phase?:"PHASE3"} (sponsor or condition required).
deliveryNoOptional delivery channels in addition to the always-on persistent feed. {email:"you@x.com"} sends a templated alert per fired event. {sms:"+15551234567"} sends an SMS per event — must match the verified phone on the caller's account (verify at https://pipeworx.io/account first; 10/day cap). {webhook:"https://..."} POSTs each event JSON to your endpoint, HMAC-signed — the response includes delivery.webhook_secret (whsec_…) ONCE; verify X-Pipeworx-Signature = sha256 HMAC of "<X-Pipeworx-Timestamp>.<raw body>". Auto-disabled after 10 consecutive failing runs.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Disclosures beyond annotations: subscription creation is a write operation (consistent with readOnlyHint=false), returns ID, requires specific account type, mentions rate limits (10/day SMS), and webhook signing secret returned once. No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Dense but well-structured with clear topic sentences. Could be slightly more concise or organized into bulleted sub-sections, but front-loads the main action and progresses logically.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers almost all aspects: creation, types, delivery, requirements. Lacks explicit return format for non-webhook deliveries, but consistent with no output schema. Persistent feed mention helpful. Highly complete for a complex tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, and the description adds significant value: explains type-specific params with examples, delivery constraints (verified phone, email pattern, webhook restrictions), and default feed. Enhances schema significantly.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool creates a proactive monitoring subscription to a live-data event stream and returns a subscription ID. It distinguishes from sibling tools like list_subscriptions and unsubscribe by specifying creation. Examples of supported types and delivery channels reinforce purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides clear context: requires Pipeworx OAuth account, lists supported types with examples, and delivery options. Implicitly distinguishes from alternatives like list_subscriptions. Could be more explicit about when not to use or prior setup like phone verification, but overall adequate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.8/5.0
Disambiguation3/5

Most tools have clearly described distinct purposes, but a few near-duplicates exist: ask_pipeworx and ask_pipeworx_beta are functionally identical right now, and ai_visibility_check vs scan_competitor_ai_presence overlap. The polymarket sub-family also has multiple edge/fill tools that could be confused.

Naming Consistency3/5

The naming is varied but readable. Many tools follow verb_noun (ask_pipeworx, resolve_entity, search_within, subscribe), yet several are noun phrases (entity_profile, recent_changes, polymarket_edges, bet_research, pipeworx_feedback). There's no single coherent pattern, but the mixture is not chaotic.

Tool Count2/5

At 33 tools, the server is oversized for typical MCP coherence. The breadth is broad (prediction markets, healthcare datasets, memory, subscriptions), but such a large count forces agents to filter through many utilities (suggest_questions, discover_tools, generate_llms_txt) that could be consolidated or hidden.

Completeness4/5

The domain—data querying and analysis—is well covered: universal routing (ask_pipeworx), grounded verification, deep research, entity resolution, dataset metadata, subscriptions, prediction-market edge checks, and memory tools. Minor gaps exist (e.g., no direct health-care-specific analytics batch or file download), but no major dead ends for core workflows.

Resources