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Data Austin

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

A4.7/5.0
Behavior5/5

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

Annotations indicate readOnlyHint=false, idempotentHint=true, destructiveHint=false. The description adds significant behavioral context: OAuth requirement, type-specific parameters, delivery constraints (SMS cap, webhook auto-disable), and the always-on feed. 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?

The description is detailed and front-loaded with the purpose, but each sentence adds value. Slightly verbose in the delivery section, but overall well-structured for a complex tool.

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

Completeness5/5

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

For a tool with 3 parameters and no output schema, the description covers all aspects: purpose, requirements, types, parameters, delivery options, constraints, and return value. It is complete and contextual.

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%, but the description greatly expands on each parameter with concrete examples, required fields, and additional constraints (e.g., webhook signing, SMS verification). It adds meaning beyond the schema definitions.

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 lists supported types and delivery channels, distinguishing it from sibling tools like list_subscriptions and unsubscribe.

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?

The description explicitly requires a Pipeworx OAuth account, noting that anonymous and BYO accounts cannot persist subscriptions. It implies use for creation versus listing/unsubscribing, though it does not explicitly state when not to use.

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

A4/5.0
Disambiguation3/5

Many tools have overlapping purposes, such as multiple ask_pipeworx variants (beta, grounded) and several prediction market tools (arbitrage, edges, fill risk, spread). While descriptions help differentiate them, the abundance of similar tools makes it easy for an agent to misselect.

Naming Consistency3/5

Tool names are a mix of snake_case with inconsistent prefixes: some use 'ask_', 'polymarket_', 'austin_', while others are isolated verbs (forget, remember) or compound nouns (entity_profile). The pattern is not uniform but still readable.

Tool Count3/5

With 34 tools, the server is heavy. Although each tool seems justified for its niche, the set could be consolidated (e.g., merging ask_pipeworx variants) to reduce clutter. The count feels slightly excessive for the scope.

Completeness4/5

The server covers a broad range of domains: Austin open data, pipeworx data, prediction markets, memory management, and subscriptions. Core workflows are well-supported, with only minor gaps like a missing cross-source search tool.

Resources