local-only server

The server can only run on the client’s local machine because it depends on local resources.

Integrations

Uses Docker to run the Qdrant vector database which stores the persistent memories created by the model.
Provides project sponsorship capabilities through GitHub Sponsors.
Offers support for the project through Ko-fi donations.

FEGIS

FEGIS is a runtime framework for structured cognition and persistent cognitive artifacts in language models built with Anthropic's Model Context Protocol. It allows schema-defined cognitive modes to be dynamically registered, invoked, and stored as structured cognitive artifacts using vector embeddings and semantic context. Think: programmable thinking tools with recallable cognitive artifacts.

FEGIS is not a cognitive system — it's the foundation for building your own.

In FEGIS, cognition refers to the structured use of dynamic tools (called modes) to capture, evaluate, and relate thoughts. These tools are defined in archetypes and allow the model to engage in different types of cognitive activity such as reflection, awareness, and analysis. Rather than simulating cognition through unstructured prompting, FEGIS enables schema-driven cognition where every thought becomes a searchable, persistent, and context-rich artifact.

Key Capabilities

Schema-Defined Cognition: Define custom cognitive modes in YAML with structured fields and metadata
Persistent Cognitive Artifacts: Store cognitive artifacts with full provenance (mode, UUID, timestamp, metadata)
Semantic Retrieval: Search for previous cognitive artifacts by content similarity or direct UUID lookup
Vectorized Storage: Utilize embeddings for efficient semantic search across artifacts
Model-Agnostic Format: Your cognitive artifacts persist across different models and sessions

What FEGIS Enables

Develop agents that reference, reflect on, and build upon prior cognitive artifacts
Own a fully local, portable, and inspectable Cognitive Archive
Maintain a persistent, structured body of thought that can be searched, retrieved, and extended over time
Layer modes of cognition to support emergent tool use

Architecture

FEGIS consists of several key components:

Archetype Definitions: YAML files that define cognitive modes and their structure
Model Context Protocol Server: Exposes cognitive tools to compatible LLM clients
Qdrant Vector Database: Stores and indexes cognitive artifacts for semantic retrieval
Dynamic Tool Registration: Creates MCP tools from archetype definitions at runtime

Quickstart

1. Install `uv` and clone the repo

# Install uv (modern Python package/runtime manager)

# macOS/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

# Windows
winget install --id=astral-sh.uv -e

# Clone the repo
git clone https://github.com/p-funk/FEGIS.git

2. Install and start Qdrant

Make sure Docker is installed and running:

docker run -d --name qdrant -p 6333:6333 -p 6334:6334 qdrant/qdrant:latest

If you need to install Docker:

Download Docker Desktop

3. Configure Claude Desktop

Create or edit the Claude Desktop config file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

Paste the following, and replace the placeholder path with the full path to your local FEGIS clone:

{
  "mcpServers": {
    "mcp-fegis-server": {
      "command": "uv",
      "args": [
        "--directory",
        "<FEGIS_PATH>",
        "run",
        "fegis"
      ],
      "env": {
        "QDRANT_URL": "http://localhost:6333",
        "QDRANT_API_KEY": "",
        "COLLECTION_NAME": "cognitive_archive",
        "FAST_EMBED_MODEL": "nomic-ai/nomic-embed-text-v1.5",
        "CONFIG_PATH": "<FEGIS_PATH>/archetypes/example.yaml"
      }
    }
  }
}

Creating Custom Archetypes

FEGIS is fundamentally a framework for implementing cognitive architectures. The example archetype provided is just one possible configuration focusing on introspective thought processes.

You can create your own custom archetypes by:

Creating a new YAML file in the archetypes directory
Defining your own cognitive modes, fields, and facets
Updating the CONFIG_PATH in the Claude Desktop configuration

For detailed guidance on designing effective archetypes, see Effective FEGIS Archetype Design.

For example, you could create archetypes for:

Problem-solving processes
Creative workflows
Analytical thinking frameworks
Domain-specific reasoning patterns

Using FEGIS Tools

FEGIS tools are made available to the model at runtime, but they are not used automatically.

Tool Priming

To encourage a model to use the cognitive tools, you must first prime it with appropriate instructions. For example.yaml:

  Throughout our conversation, use your tools naturally and fluidly. 
  Feel free to reflect, introspect, stay aware, have an innermonologue
  or use cognitive artifacts to recall past insights as needed. You can search past
  thoughts using `fegis_search`, or revisit specific artifacts with
  `fegis_retrieve`.

Each archetype file included in the repo has it's own Priming Prompt that will get you started.

Cognitive Artifact Usage

The cognitive artifact system allows for:

Semantic Search: Find cognitive artifacts based on content similarity
Direct Retrieval: Look up specific artifacts by their UUID
Persistent Storage: Artifacts remain available across sessions and models

License

Licensed under the PolyForm Noncommercial License 1.0.0.

Free for personal and non-commercial use
Commercial license required for resale, integrations, or hosted services

Contact goldenp@ptology.com for commercial licensing.

Support

☕ Buy me a coffee
💖 Sponsor on GitHub

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FEGIS is a Model Context Protocol server that gives LLMs structured, persistent and portable memory through customizable cognitive tools defined in schema.