argumentation-logic-engines
A suite of computational modules engineered to foster rigorous, structured reasoning by allowing AI agents to methodically construct, dispute, and synthesize logical propositions within a formalized dialectical structure. This infrastructure aids in refining judgment across complex domains such as ethical predicaments, regulatory assessment, and scientific model validation through explicit visualization and mapping of inferential dependencies.
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waldzellai
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Cognitive Augmentation Protocol Servers
An ensemble of Model Context Protocol (MCP) services designed to significantly augment the intellectual capabilities of large language models.
Contained Servers
This consolidated repository hosts the following specialized MCP servers:
- Formal Dialectics - Dedicated to systematic, structured argumentative discourse.
- Spatial Cognition - For processing and rendering diagrammatic thought constructs.
- Empirical Validation - For managing hypothesis testing cycles and evidence appraisal.
- Metaphorical Mapping - For structured development of analogical comparisons.
- Self-Monitoring Logic - For internal knowledge state inspection and certainty quantification.
- Choice Architecture - For prescriptive, structured analysis of alternative outcomes.
- Distributed Consensus - For facilitating multi-party problem resolution and perspective integration.
- Moral Calculus - For assessing actions against established ethical parameters.
- Linguistic Anomaly Detector - For identifying potentially slanted or prejudiced expressions.
- Constraint Satisfaction Unit - For verifying adherence to logical and quantitative boundaries.
- Conceptual Outliner - For drafting rudimentary sequential narratives.
- Objective Progression Manager - For tracking and ensuring the fulfillment of defined targets.
- Sensory Integration Processor - For harmonizing textual data with visual descriptors.
Prospective Enhancements
Future development is considering the integration of these specialized capabilities:
- Affective Responsiveness - Implements sentiment tracking to enable adaptive, emotionally congruent conversational flows.
- Context Persistence Layer - Establishes long-duration memory stores for maintaining continuity across disparate interaction sessions.
Deployment
Individual components are accessible via standard package managers:
bash
npm installation path
npm install @waldzellai/cognitive-augmentation-suite
yarn installation path
yarn add @waldzellai/cognitive-augmentation-suite
Integration with Desktop Runtime
Configuration requires updating the local runtime manifest (claude_desktop_config.json):
{ "mcpServers": { "formal-dialectics": { "command": "npx", "args": [ "-y", "@waldzellai/cognitive-augmentation-suite" ] } } }
Containerization
All services are packaged as accessible Docker artifacts:
bash docker run --rm -i waldzellai/cognitive-augmentation-suite
Project Contribution
To participate in development, clone the primary repository and establish the environment:
bash git clone https://github.com/waldzellai/model-enhancement-servers.git cd model-enhancement-servers npm install
Execute the build script for all component packages:
bash npm run build
Licensing
This codebase is distributed under the terms of the MIT License (refer to the LICENSE file for specifics).
