Skip to main content
Glama
ocbenji

@bitcoinbenji/mcp

ai_longform

Summarize very long documents up to 50K words in a single flat-fee call. Condense lengthy texts without per-word charges.

Instructions

Summarize huge documents (~50K words) in one flat-fee call. [75 sats per call]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textNo
urlNoalternative to text — fetches & summarizes a URL
focusNospecific focus area (optional)
max_lengthNomedium
preimageNo(L402 mode) Preimage from paid Lightning invoice — only needed if no API key is set
macaroonNo(L402 mode) Macaroon from the previous 402 challenge
Behavior2/5

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

No annotations provided, so description carries full burden. It mentions flat-fee and cost but does not disclose behavioral traits like how summaries are generated, limitations, error handling, or return format. L402 payment mode is hinted but not explained.

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?

Two sentences, concise with key info: purpose and cost. No wasted words, but could benefit from a brief usage note.

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

Completeness2/5

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

With 6 parameters (none required), no output schema, and no annotations, the description is too sparse. Missing guidance on payment (L402), how to choose between text/url, and what to expect in response.

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

Parameters3/5

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

Schema coverage is 67%, and description adds context about large documents and cost. However, it does not clarify the relationship between 'text' and 'url' parameters or how 'focus' affects output. Baseline 3 with moderate added value.

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 'Summarize huge documents (~50K words) in one flat-fee call', which specifies the action (summarize), resource (huge documents), and differentiates from siblings like ai_summarize by emphasizing scale and pricing.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use for large documents but does not explicitly state when to use this tool over alternatives like ai_summarize, nor when not to use it. No direct guidance on prerequisites or exclusions.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ocbenji/bitcoinbenji-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server