HUMMBL MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Capabilities
Features and capabilities supported by this server
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| prompts | {
"listChanged": true
} |
| resources | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_modelA | Retrieve detailed information about a specific HUMMBL mental model using its code (e.g., P1, IN3, CO5). |
| list_all_modelsB | Retrieve complete list of all 120 HUMMBL mental models with basic information. |
| search_modelsA | Search HUMMBL mental models by keyword across codes, names, and definitions. |
| get_transformationA | Retrieve information about a specific transformation type and all its models (P, IN, CO, DE, RE, SY). |
| search_problem_patternsB | Find pre-defined problem patterns with recommended transformations and top models based on a search query. |
| recommend_modelsC | Get recommended mental models based on a natural language problem description using HUMMBL REST API. |
| get_related_modelsC | Get all models related to a specific model with relationship details |
| add_relationshipC | Add a relationship between two mental models with evidence. |
| get_recommendation_historyA | Fetch the caller's past recommendation calls (problems submitted and the model codes that were returned), newest first. Useful for 'what did we explore last time?' and for avoiding re-recommending the same models. |
| get_methodologyA | Retrieve the canonical Self-Dialectical AI Systems methodology with HUMMBL Base120 mappings. |
| audit_model_referencesB | Audit a list of HUMMBL model references for existence, transformation alignment, and duplicates. |
| list_workflowsA | Get all available guided workflows for problem-solving with Base120 mental models. |
| start_workflowB | Begin a guided multi-turn workflow for systematic problem-solving using Base120 mental models. |
| continue_workflowA | Proceed to the next step of your guided workflow after completing the current step. |
| find_workflow_for_problemB | Discover which workflow best fits your problem type or situation. |
| export_modelsA | Export a curated subset of Base120 mental models as Markdown, JSON, or PDF. Pass |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| root_cause_analysis | Systematically investigate problems to find root causes, not just symptoms. Uses Perspective, Inversion, and Decomposition transformations. (~20-30 minutes) |
| strategy_design | Design comprehensive strategies by framing the problem, combining elements creatively, and understanding system dynamics. (~30-45 minutes) |
| decision_making | Make high-quality decisions by framing clearly, stress-testing with inversion, and planning reversible vs. irreversible choices. (~15-25 minutes) |
| analyze_with_models | Open-ended analysis: surface the most relevant Base120 mental models for a problem and synthesise them into concrete guidance. |
| apply_model | Apply one specific HUMMBL mental model (by code, e.g. P1, IN3, CO5) to a problem. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| all-models | Complete Base120 framework with all 120 mental models. |
| self-dialectical-methodology | Canonical Self-Dialectical AI Systems methodology with HUMMBL Base120 mappings. |
| self-dialectical-methodology-markdown | Human-readable markdown overview of the Self-Dialectical AI Systems methodology, derived from the canonical structured definition. |
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