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openbci-mcp

openbci-mcp

by sandraschi
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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agentic_openbci_workflow

Automates multi-step OpenBCI workflows from natural language prompts. Connects boards, streams data, and processes signals without manual setup.

Instructions

Multi-step OpenBCI workflows via FastMCP sampling (SEP-1577).

Example: agentic_openbci_workflow( workflow_prompt="Connect synthetic board, start stream, compute band power", available_tools=["openbci_board", "openbci_stream", "openbci_signal"], )

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "workflow_prompt": "<workflow_prompt>"
    },
    "name": "agentic_openbci_workflow"
  }
}

Input Schema

NameRequiredDescriptionDefault
max_iterationsNoMax sample_step rounds.
available_toolsNoopenbci_* tool names to expose to the sampler.
workflow_promptYesGoal in natural language, e.g. 'Connect Cyton on COM3, stream, report beta power'.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description must carry full weight. It mentions internal mechanism (FastMCP sampling) and exposes max_iterations and available_tools, but does not disclose safety, authentication, or failure behavior.

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 very concise: two sentences and an example. It is front-loaded with the core purpose and wastes no words.

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

Completeness3/5

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

For a complex orchestrator with no output schema, the description lacks details on return value, error handling, and edge cases. It covers the high-level purpose but is incomplete for an agent to fully understand its behavior.

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 100%, so baseline is 3. The description adds no extra meaning beyond what the schema already provides for each parameter.

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 it's a multi-step workflow orchestrator via FastMCP sampling, with an example that distinguishes it from sibling individual tools like openbci_board or openbci_stream.

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 example implicitly shows when to use it (for multi-step tasks), but it lacks explicit when-not-to-use or alternative guidance. The sibling relationship helps.

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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