cognigy-ai-mcp-management-server

inject_context

Inject context data into a Cognigy.AI session to set user data, preferences, or state before or during conversations. Context is shared state accessible by flow nodes.

Instructions

Injects context data into a Cognigy.AI session. Context is shared state accessible by flow nodes. Use this to set user data, preferences, or state before/during conversations.

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": {
      "sessionId": "<sessionId>",
      "userId": "<userId>",
      "context": "<context>"
    },
    "name": "inject_context"
  }
}

Input Schema

Name	Required	Description
`userId`	Yes	The user ID for the session
`context`	Yes	The context object to inject (key-value pairs)
`sessionId`	Yes	The session ID to inject context into

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.4Jul 27, 2026

TDQS

A4/5.0

Behavior3/5

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

Annotations already indicate non-read-only, non-idempotent, non-destructive. Description adds that context is shared state, but lacks details on merge vs overwrite 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?

Two focused sentences: first defines action, second provides usage context. No filler.

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?

Despite no output schema, the tool is simple and the description adequately covers purpose and when to use. Could mention merge behavior, but not critical.

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 covers 100% of parameters with descriptions. Description adds general usage context but no additional parameter-specific meaning.

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 'injects' and resource 'context data into a Cognigy.AI session', and distinguishes from sibling 'reset_context' by focusing on setting state.

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?

Provides explicit guidance to 'set user data, preferences, or state before/during conversations', but does not mention alternatives like 'reset_context' or when not to use.

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

Deploy Server