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Chembl

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?

The description substantially enriches the annotation hints. It discloses the OAuth requirement, the 10/day SMS cap, phone verification prerequisites, webhook auto-disable after 10 consecutive failures, and that the webhook signing secret is returned only once. These are behavioral traits not present in the annotations and are critical for safe invocation.

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

Conciseness5/5

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

The description is dense but efficiently organized: purpose first, then prerequisites, then supported types, then delivery channels. Every sentence adds distinct value (e.g., caps, verification steps, webhook signing details) without repetition or filler. It is appropriately sized for a complex tool with nested parameters.

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?

Given the tool's complexity (3 parameters, nested objects, 5 subscription types, multiple delivery channels) and lack of an output schema, the description is remarkably complete. It explains return value (subscription id), authentication needs, per-type params, delivery behavior, and failure semantics. No obvious gap remains for an agent to invoke it correctly.

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 descriptions (100% coverage), but the description adds meaning via concrete examples for each subscription type, delivery channel specifics, and constraints like E.164 phone format and webhook HTTPS-only. This goes beyond the schema's surface-level definitions, though the schema already carries much of the semantic weight.

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 opens with a specific verb+resource: 'Create a proactive monitoring subscription to a live-data event stream.' It clearly differentiates from sibling tools like list_subscriptions and unsubscribe by focusing on the creation act, and enumerates concrete subscription types and delivery channels that make its scope unmistakable.

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 gives clear context for when to use the tool: it requires a Pipeworx OAuth account, explains that anonymous/BYO cannot persist subscriptions, and provides type-specific examples. It does not explicitly name alternatives (e.g., 'use recent_alerts for pulling'), but it instructs users to pull the feed via recent_alerts or the registry URL, implying a monitoring creation role.

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

B3.4/5.0
Disambiguation2/5

The tool list mixes a small ChEMBL dataset with a large Pipeworx toolkit, and several Pipeworx tools are near-duplicates (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded; polymarket_arbitrage, polymarket_edges, polymarket_fill_risk). An agent would struggle to pick the right tool among overlapping prediction-market and research tools, and the ChEMBL tools are buried under irrelevant functionality.

Naming Consistency2/5

Naming conventions are mixed: ChEMBL tools use bare nouns (molecule, target, activities) while Pipeworx tools use inconsistent verb_noun phrases (ask_pipeworx, validate_claim) and noun phrases (entity_profile, recent_changes). There is no predictable pattern across the set.

Tool Count2/5

37 tools is far too many for a server named 'Chembl', especially since the majority are unrelated Pipeworx features. The count is justified neither by the apparent ChEMBL scope nor by a coherent overall purpose, making the server feel bloated and unfocused.

Completeness3/5

The ChEMBL subset is reasonably complete (search, molecule, target, activities, mechanism, drug_indications), and the Pipeworx side includes broad research/data tools, but the set lacks a unified purpose. Gaps include no direct assay/detail retrieval and no coherent lifecycle across the mixed domains.

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