Skip to main content
Glama
ocbenji

@bitcoinbenji/mcp

ai_research

Searches the web in multiple steps to compile a cited synthesis answer from your question and chosen sources.

Instructions

Multi-step web research + cited synthesis. [100 sats per call]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
questionYes
max_sourcesNo
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
Behavior3/5

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

With no annotations, the description carries full behavioral disclosure burden. It mentions 'multi-step' and 'cited synthesis,' indicating iterative web searches and citation output. However, it omits details such as how many steps, what happens on failure, authentication requirements (preimage/macaroon in schema but not described), or output format. This is adequate but not rich.

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 concise at one line plus cost note, front-loading the core purpose. Every word earns its place. While slightly terse, it remains effective and well-structured.

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?

The tool is moderately complex (multi-step web research with citations) and lacks an output schema. The description does not explain the output format, limitations, or typical usage context. This leaves significant gaps for an agent to fully understand the tool's behavior.

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

Parameters2/5

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

Schema coverage is 50% (preimage and macaroon described in schema). The description adds no parameter explanations; it does not clarify 'question' or 'max_sources' beyond their types/defaults. With no added parameter context, and baseline 3 reduced due to missing coverage, a score of 2 is appropriate.

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 'Multi-step web research + cited synthesis,' which is a specific verb-resource combination. It distinguishes well from sibling tools like ai_scrape (single-page scraping) and ai_summarize (summarization of provided text) by emphasizing multi-step research and citation generation.

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

Usage Guidelines2/5

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

The description does not specify when to use this tool versus alternatives like ai_agent or ai_scrape. It provides no when-to-use or when-not-to-use guidance, and no mention of prerequisites or context. The cost hint is useful but insufficient for usage decisions.

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