Skip to main content
Glama

attach_processor

Attach a processor to an EEG session. Streaming processors run on every chunk for low-latency closed-loop logic; non-streaming processors run only when explicitly called.

Instructions

Attach a processor to a session.

A streaming processor runs inside the acquisition loop on every chunk, so it reacts within one poll interval without an agent round-trip -- that is how closed-loop logic gets fast. The cost is that slow code stalls acquisition; processor_status reports each one's mean and worst-case time so you can see whether yours is affordable.

Non-streaming processors do nothing until you call run_processor.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsNoProcessor-specific settings; see its ``params`` in the listing.
processorYesName from list_processors.
session_idYesThe session to attach to.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains the behavioral differences between streaming and non-streaming modes, describes the performance implications (mean and worst-case times via processor_status), and notes the operational consequence (slow streaming code stalls acquisition). It doesn't cover edge cases like duplicate attachments or error handling, but the core behavioral traits are well disclosed.

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 well-structured and efficient, with a clear opening sentence followed by two focused paragraphs explaining streaming and non-streaming behavior. Every sentence adds value—none are filler. The use of code-formatted tool names ties it to other tools without wasting words.

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

Completeness4/5

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

The tool has 3 parameters (100% schema covered) and an output schema, so much is handled by structured data. The description explains the critical semantic distinction (streaming vs non-streaming) that affects usage decisions. It could mention what the output/return value contains, but given that an output schema exists, this is adequately complete.

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

Parameters4/5

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

Schema coverage is 100%, so the schema already documents all three parameters. The description adds context beyond the schema: it clarifies how the streaming vs non-streaming distinction relates to behavior, which helps the agent understand the implications of choosing certain processor types. However, it doesn't directly elaborate on the params field beyond what the schema says ('see its params in the listing').

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 the tool's purpose: "Attach a processor to a session." It distinguishes this from sibling tools like run_processor, detach_processor, and processor_status by explaining the attach action explicitly. The distinction between streaming and non-streaming processors further clarifies what this tool accomplishes.

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

Usage Guidelines5/5

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

The description provides excellent usage guidance by distinguishing when each mode is appropriate: streaming for closed-loop logic requiring fast reaction within a poll interval, while noting the trade-off (slow code stalls acquisition). It also names related tools (processor_status, run_processor) that complement or follow this one, giving the agent clear context on when to use this vs alternatives.

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/AImplifier/eeg-mcp'

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