The MCP server exposes the ΛXIØM Kernel as callable tools for agent clients. Use it when an agent needs structural decomposition, governed prompt/response checks, operator selection, coherence reads, canon lookup, world-model memory, or gap analysis without importing kernel source code.
Keep the boundary clear: MCP is a local or self-hosted kernel tool surface. ΛXIØM Lens Console owns hosted API identity, keys, usage, and the decision ledger. MCP uses its own process configuration and local ledgers unless an operator explicitly integrates it with the hosted service.
Simple setup
- Create an API key in console.axiomlens.com/dashboard/keys. Use that key for backend HTTP calls to
api.axiomlens.com. - Clone or install
axiom-kernel-core on the machine running Claude Desktop, Cursor, Gemini, or another MCP client. The MCP entrypoint is mcp-servers/axiom-kernel-mcp/server.py. - Paste an
mcpServers block into the client config, set provider credentials in the MCP server environment, restart the client, and call tools such as kernel_govern_input, kernel_govern, and gap_analyze.
Customer-facing rule: API Keys are for hosted server/backend HTTP integration. MCP is for local or self-hosted agent, IDE, and tool integration. Using both does not automatically join their credentials or telemetry.
Copy-paste starter config
Replace the paths and provider key, then restart the MCP client. Use this for local agent/IDE setup; do not treat it as a hosted public MCP URL.
{
"mcpServers": {
"axiom-kernel": {
"command": "python",
"args": [
"/path/to/axiom-kernel-core/mcp-servers/axiom-kernel-mcp/server.py"
],
"env": {
"AXIOM_LLM_PROVIDER": "openai",
"AXIOM_LLM_API_KEY": "sk-...",
"AXIOM_LLM_MODEL": "gpt-4o-mini",
"AXIOM_WORLD_MODEL_PATH": "/tmp/axiom_world_model.json"
}
}
}
}
Local STDIO configuration
For Claude Desktop, Cursor, Gemini, Codex-compatible clients, or any MCP client that launches local commands, point the client at the kernel MCP server file from the kernel checkout:
{
"mcpServers": {
"axiom-kernel": {
"command": "python",
"args": [
"/path/to/axiom-kernel-core/mcp-servers/axiom-kernel-mcp/server.py"
],
"env": {
"AXIOM_LLM_PROVIDER": "stub",
"AXIOM_LLM_MODEL": "",
"AXIOM_WORLD_MODEL_PATH": "/tmp/axiom_world_model.json"
}
}
}
}
Remote or multi-project SSE
For remote access, run the same server in SSE mode and put normal network controls around it. The server process owns provider credentials through environment variables; clients call tools through MCP.
cd /path/to/axiom-kernel-core
python mcp-servers/axiom-kernel-mcp/server.py --sse --host 0.0.0.0 --port 8420
# SSE-capable MCP clients connect to:
# http://localhost:8420/sse
Environment variables
| Variable | Default | Purpose |
|---|
AXIOM_LLM_PROVIDER | stub | stub, openai, anthropic, or ollama |
AXIOM_LLM_MODEL | empty | Model name for the configured provider |
AXIOM_LLM_API_KEY | empty | Provider key for OpenAI or Anthropic modes |
AXIOM_LLM_BASE_URL | empty | Ollama or custom provider base URL |
AXIOM_WORLD_MODEL_PATH | unset | JSON file path for persistent world model memory |
AXIOM_SIGNAL_LEDGER_PATH | unset | Optional signal ledger JSONL path |
AXIOM_ACCESS_LEDGER_PATH | unset | Optional access audit JSONL path |
Tool groups
| Group | Tools | Use when |
|---|
| Cycle processing | kernel_processkernel_chainkernel_decomposekernel_statuskernel_diagnosticskernel_models
| Run the 10+Ø cycle, inspect decomposition, check subsystem state, and choose per-request model presets. |
| Governance sandwich | kernel_govern_inputkernel_govern
| Validate prompts before a model call and govern draft responses after generation. |
| Operators and coherence | kernel_operatorkernel_coherencekernel_inferkernel_last_sro
| Select an operator, inspect contradictions, run structural inference, and read the last Structural Resolution Object. |
| Canon and patterns | kernel_lawskernel_atomskernel_patterns
| Query AXIØM laws, semantic atoms, and pattern stores without coupling an app to kernel internals. |
| Memory and gap analysis | world_model_queryworld_model_summaryworld_model_graphgap_analyze
| Query persistent structural memory and report genuinely missing fields instead of guessing. |
| Audit and operations | kernel_configureaccess_audit_statsaccess_audit_eventsaccess_audit_actorssignal_ledger_timelinesignal_ledger_stats
| Configure runtime state, inspect MCP access, and review recent signal ledger activity. |
Governed app pattern
- Call
kernel_govern_input on the user prompt before sending it to a model. - Call your model or the ΛXIØM HTTP API using the server-side credential boundary.
- Call
kernel_govern on the draft answer and preserve the returned governance metadata. - Use
kernel_laws, kernel_atoms, kernel_patterns, kernel_coherence, or gap_analyze when the agent needs a diagnostic read instead of free-form advice.