Skip to main content
Glama

Oxylabs

by io.github.pipeworx-io

Subscribe to Alerts

subscribe
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?

Beyond annotations, the description adds critical behavioral details: requires Pipeworx OAuth account, delivery channels with constraints (SMS cap, webhook auto-disable), and return of subscription id. No contradiction 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 well-structured with front-loaded purpose and detailed specifics. It is slightly lengthy but each sentence adds value; could be more concise with bullet points.

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 (multiple types, delivery options, prerequisites, limitations), the description covers all essential aspects. No output schema but return value is mentioned.

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?

With 100% schema coverage, the description adds substantial meaning: examples for each type, item codes significance, delivery constraints (verified phone, cap), and webhook signing. This goes well beyond the schema.

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 that this tool creates a proactive monitoring subscription to a live-data event stream and returns a new subscription id. It distinguishes itself from sibling tools like list_subscriptions and unsubscribe by focusing on creation.

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 context for when to use the tool (create subscriptions) and mentions prerequisites (OAuth account) but does not explicitly contrast with sibling tools. However, the sibling list allows inference.

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

All Oxylabs toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4/5.0
Disambiguation3/5

Several tools overlap in purpose, particularly the ask_pipeworx family (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) where beta currently matches stable exactly, and the polymarket_* cluster with similar names. However, detailed descriptions clarify each tool's specific role, so an agent can usually select correctly with careful reading.

Naming Consistency3/5

All names use snake_case and are generally descriptive, but they mix conventions: many are verb_noun (list_subscriptions, validate_claim), while others are noun phrases (entity_profile, recent_changes). Prefixes like oxylabs_ and polymarket_ are consistent, but the lack of a uniform verb-first pattern reduces predictability.

Tool Count2/5

With 34 tools, the server exceeds the 25-tool threshold for 'too many'. While the broad scope (data lookup, scraping, prediction markets, memory, subscriptions) warrants a larger surface, the sheer number makes it difficult for agents to quickly identify the right tool without extensive scanning.

Completeness4/5

The tool set covers the core domain thoroughly: question answering, deep research, entity resolution, comparison, validation, web scraping, prediction market analysis, memory management, and subscriptions. Minor gaps like limited e-commerce scraping beyond Amazon and no direct data-writing tools exist, but they do not critically hamper workflows.

Resources