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SecondBrain MCP

SecondBrain MCP

by vladilenm
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

get_project_context

Retrieve full project context including README, related notes, open tasks, and linked decisions to understand a project's purpose and status.

Instructions

Full context for a project: README content + related notes (via wikilinks) + open tasks + linked decisions. The key tool for understanding what a project is about.

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": {
      "project": "<project>"
    },
    "name": "get_project_context"
  }
}

Input Schema

NameRequiredDescriptionDefault
projectYesProject path, name, or alias

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the content returned (README, notes, tasks, decisions) but does not mention behavioral traits like read-only status, performance, or any side effects. The description is partially transparent but lacks important behavioral context.

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 extremely concise: one sentence plus a summarizing second sentence. It front-loads the key information and contains no wasted 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?

Given the complexity of the tool (aggregating multiple data types) and the absence of an output schema, the description adequately explains what the tool returns. It could optionally include more detail about the output structure, but it is sufficient for understanding the tool's purpose.

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 description coverage is 100% for the single parameter 'project', with a clear description in the schema. The description does not add additional meaning beyond what the schema provides, so it meets the baseline of 3.

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 verb 'get' and the resource 'context for a project', and enumerates specific components: README content, related notes, open tasks, linked decisions. It distinguishes itself from sibling tools like get_note or list_projects by aggregating multiple aspects.

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 description explicitly calls this 'the key tool for understanding what a project is about', which conveys when to use it. However, it does not provide explicit guidance on when not to use it or mention alternative tools for more specific queries.

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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