agentfuel402
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| fuel_b2b_leadsB | Fetches live B2B buying intent signals from Show HN with detected tech stacks, domains, and Intent Scores (30-100). Cost: $0.010 USDC via x402. |
| fuel_clean_markdownA | Fetches any public URL, strips noise/scripts/ads, sanitizes prompt injections, and returns clean Markdown and token estimates. Cost: $0.005 USDC via x402. |
| fuel_ecom_price_stockA | Extracts live price, currency, in-stock status, SKU, and discount delta for Shopify, WooCommerce, and Schema.org product URLs. Cost: $0.005 USDC via x402. |
| fuel_sdk_specA | Queries live PyPI or npm registry metadata for latest stable version, license, and dependency count. Cost: $0.005 USDC via x402. |
| fuel_reverse_engineerA | Detects frameworks, hidden REST/GraphQL endpoints, hydration state, and generates OpenAPI 3.1 specs for a target URL. Cost: $0.020 USDC via x402. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 5 tools
Each tool targets a clearly distinct data need: B2B leads, clean Markdown extraction, e-commerce price/stock, package registry metadata, and reverse engineering. The two URL-fetching tools (fuel_clean_markdown and fuel_reverse_engineer) could overlap superficially, but their outputs and use cases are explicitly differentiated.
All tools consistently use the fuel_ prefix and snake_case, which makes the set easy to scan. The only minor inconsistency is that some names are noun phrases (fuel_b2b_leads, fuel_sdk_spec) while others are verb phrases (fuel_clean_markdown, fuel_reverse_engineer).
Five tools is well-scoped for a focused paid data-extraction API. Each tool covers a distinct capability without obvious redundancy or padding.
The set covers a solid range of web data tasks: lead discovery, content cleaning, e-commerce extraction, package metadata, and endpoint reverse engineering. There are minor gaps such as generic structured extraction or batch operations, but the core lifecycle for the stated purpose is covered.