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Crypto Feeds

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?

Annotations already indicate non-read-only, non-destructive, idempotent, and open-world behavior. The description adds substantial context: the requirement for OAuth, details on supported event types, SMS verification and caps, webhook signing and auto-disable after 10 failures, and the return of a subscription id. This goes well beyond the annotations and fully discloses important behavioral traits.

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 long but dense with relevant information, structured into supported types and delivery channels. It front-loads the core purpose and uses concise lists. While some might consider it verbose, every sentence delivers necessary detail, making it efficient rather than bloated.

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 nested objects and no output schema, the description is remarkably complete: it states the return value, prerequisites, per-type parameter examples, delivery channel behavior, and operational limits. It equips an agent to select and invoke the tool correctly without needing additional context.

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

Parameters4/5

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

The input schema already covers all parameters with detailed descriptions (100% coverage). The description adds practical meaning, such as interpreting items:["5.02"] as officer changes, explaining the SMS 10/day cap, and noting the webhook signing secret is returned once. These examples and clarifications enhance understanding beyond the schema, though the high schema coverage means extra credit is modest.

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 begins with a specific, action-oriented statement: 'Create a proactive monitoring subscription to a live-data event stream. Returns the new subscription id.' This clearly identifies the tool's purpose and distinguishes it from siblings like unsubscribe, list_subscriptions, and recent_alerts. It further specifies supported subscription types, making the scope unambiguous.

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 provides use context, such as requiring a Pipeworx OAuth account and noting that anonymous/BYO users cannot persist subscriptions. It also explains delivery channels and when to use them, referencing alternatives like pulling via recent_alerts. However, it does not explicitly contrast with list_subscriptions or unsubscribe, though the purpose is clear enough to infer appropriate usage.

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
Disambiguation2/5

Several tools are nearly indistinguishable in role: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are all variants of the same router, with the beta version explicitly noted as currently identical to the stable one. The six Polymarket tools also overlap heavily around edge-finding, arbitrage, and fill-risk analysis, making misselection likely.

Naming Consistency3/5

Names are uniformly snake_case and groupable into prefixes like polymarket_* and pipeworx_*, but the set does not follow a consistent verb_noun convention. Noun-first names like entity_profile and recent_alerts sit alongside verb-first names like read_feed and validate_claim, and product-name suffixes such as ask_pipeworx_beta/grounded add further inconsistency.

Tool Count2/5

At 34 tools, the surface is well past the 25+ threshold and far broader than the 'Crypto Feeds' name suggests. The set spans feed reading, general data research, prediction markets, AI-brand visibility audits, npm dependency scanning, memory, and subscriptions, making it feel like a platform-wide dump rather than a focused MCP server.

Completeness3/5

The broad research workflow is well covered with query, grounded answer, deep research, entity profiles, comparisons, fact-checking, and entity resolution. However, feed functionality is read-only with no feed management, subscription types do not include crypto feeds despite the server name, and there is no dedicated tool for resolving the advertised pipeworx:// citation URIs.

Resources