Gikendaasowin Aabajichiganan
- javascript
4
GitHub Stars
javascript
Language
6 months ago
First Indexed
2 months ago
Catalog Refreshed
Documentation & install
Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.
Installation
Add the following to your MCP client configuration file.
Configuration
View docs{
"mcpServers": {
"nbiish-gikendaasowin-aabajichiganan-mcp": {
"command": "npx",
"args": [
"@nbiish/gikendaasowin-aabajichiganan-mcp"
],
"env": {
"YOUR_ENV_VAR": "PLACEHOLDER"
}
}
}
}Gikendaasowin Aabajichiganan MCP Server provides an adaptive cognitive processing framework that guides large language models to select effective reasoning strategies in real-time. It enables true meta-cognitive problem solving by evaluating and combining prompting techniques to tailor solutions to your specific context, goals, and constraints, improving accuracy and efficiency across diverse tasks.
How to use
You use this MCP server with your MCP client by pointing the client to the local stdio server command and then submitting your problem or task for cognitive processing. The server evaluates multiple modern prompting techniques, selects strategies dynamically, and returns cognitive processing results that you can apply directly in your workflow.
Practical usage patterns include submitting a complex question or decision problem with optional background context. The system then performs a 2-round, 6-stage cognitive deliberation and proposes an execution plan that includes how many times to apply each technique and when to re-deliberate.
How to install
Prerequisites: ensure you have Node.js and npm installed on your system.
Install dependencies, build the package, and prepare for local testing using the following commands one per line.
<code blocks are shown below in the code section of this article></code>
Additional notes
The MCP server supports a stdio-based runtime where you run a local command to start the server and then connect to it with your MCP client. No remote URL is required for this configuration when you prefer local execution.
Available tools
deliberate
An LLМ-guided cognitive enhancement framework that prompts the model to evaluate and select among 15 modern cognitive techniques using a 0.00-0.99 scoring system with a threshold rule.
