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aris-mcp

by Knuckles-Team
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aris-mcp

Software AG ARIS REST API + MCP Server + A2A Server for Agentic AI.

aris-mcp connects the agent ecosystem to an ARIS tenant (ARIS Connect / ARIS Enterprise / ARIS Cloud). It is the inbound and outbound bridge for the agent-utilities Knowledge Graph's Camunda + ARIS ↔ KG integration:

  • Inbound — the KG ARIS extractor (enrichment/extractors/aris.py) consumes this client to lift ARIS models + their EPC structure (functions → BusinessTask, rule operators → gateways, events collapsed, connections → FLOWS_TO) into the canonical ArchiMate ontology, where they reconcile with Camunda/Egeria via ALIGNED_WITH and are reasoned over in OWL/RDF.

  • Outbound — the KG process-intelligence writeback (enrichment/process_writeback.py) uses set_model_attributes to write a kg_intelligence attribute back onto ARIS models (gated by ARIS_ENABLE_WRITE).

Available MCP Tools

The table below is auto-generated from the live server — do not edit by hand.

Condensed action-routed tools (default — MCP_TOOL_MODE=condensed)

MCP Tool

Toggle Env Var

Description

aris_model

ARISTOOL

Work with ARIS models and their EPC structure.

aris_object

ARISTOOL

Write attributes on a single ARIS object.

Verbose 1:1 API-mapped tools (MCP_TOOL_MODE=verbose or both)

MCP Tool

Toggle Env Var

Description

aris_get_model

ARIS_APITOOL

Get a single model's metadata (including its attributes).

aris_list_model_attributes

ARIS_APITOOL

Get a model's attributes (used for writeback idempotency read-back).

aris_list_model_connections

ARIS_APITOOL

List the directed control-flow connections between a model's objects.

aris_list_model_objects

ARIS_APITOOL

List the EPC objects (functions/events/rule operators) of a model.

aris_list_models

ARIS_APITOOL

List models in the tenant/database (process + architecture).

aris_set_model_attributes

ARIS_APITOOL

Write/update attributes on a model (e.g. the kg_intelligence blob).

aris_set_object_attributes

ARIS_APITOOL

Write/update attributes on a single object.

2 action-routed tool(s) (default) · 7 verbose 1:1 tool(s). Each is enabled unless its <DOMAIN>TOOL toggle is set false; MCP_TOOL_MODE selects the surface (condensed default · verbose 1:1 · both). Auto-generated — do not edit.

Writes require ARIS_ENABLE_WRITE=True.

Related MCP server: Letta MCP Server

Environment Variables

Package environment variables

Variable

Example

Description

ARIS_API_BASE

http://localhost/abs/api

ARIS REST base URL (tenant API root). Default follows the ARIS Connect ABS layout.

ARIS_SSL_VERIFY

True

Verify TLS (set False for self-signed / homelab tenants)

ARIS_OAUTH_URL

—

1. OAuth2 client-credentials (preferred for ARIS Cloud / Connect)

ARIS_CLIENT_ID

—

ARIS_CLIENT_SECRET

—

ARIS_TENANT

—

ARIS_TOKEN

—

2. Static bearer token (alternative to OAuth)

ARIS_USERNAME

—

3. HTTP basic auth (alternative)

ARIS_PASSWORD

—

ARIS_PATHS_JSON

—

e.g. {"models":"v2/repository/models","model_objects":"v2/models/{model_id}/objects"}

ARIS_ENABLE_WRITE

False

Allow (gated) attribute writes back onto ARIS models (KG writeback)

TRANSPORT

stdio

stdio, streamable-http, or sse

HOST

0.0.0.0

PORT

8000

MCP_TOOL_MODE

condensed

Tool surface: condensed, verbose, or both

MCP_ENABLED_TOOLS

—

Comma-separated tool / tag allow/deny lists

MCP_DISABLED_TOOLS

—

MCP_ENABLED_TAGS

—

MCP_DISABLED_TAGS

—

DEBUG

False

PYTHONUNBUFFERED

1

ARISTOOL

True

The action-routed ARIS tools (aris_model, aris_object) share this toggle.

ENABLE_OTEL

True

OTEL_EXPORTER_OTLP_ENDPOINT

—

OTEL_EXPORTER_OTLP_PUBLIC_KEY

—

OTEL_EXPORTER_OTLP_SECRET_KEY

—

OTEL_EXPORTER_OTLP_PROTOCOL

—

EUNOMIA_TYPE

none

EUNOMIA_POLICY_FILE

mcp_policies.json

EUNOMIA_REMOTE_URL

—

Inherited agent-utilities variables (apply to every connector)

Variable

Example

Description

MCP_CLIENT_AUTH

—

Outbound MCP auth (oidc-client-credentials for fleet calls)

OIDC_CLIENT_ID

—

OIDC client id (service-account auth)

OIDC_CLIENT_SECRET

—

OIDC client secret (service-account auth)

MCP_URL

http://localhost:8000/mcp

URL of the MCP server the agent connects to

PROVIDER

openai

LLM provider for the agent

MODEL_ID

gpt-4o

Model id for the agent

ENABLE_WEB_UI

True

Serve the AG-UI web interface

30 package + 7 inherited variable(s). Auto-generated from .env.example + the shared agent-utilities set — do not edit.

Every variable the server reads, grouped by concern.

Connection & Credentials

Variable

Purpose

Default

ARIS_API_BASE

ARIS REST base URL (tenant API root)

http://localhost/abs/api

ARIS_SSL_VERIFY

verify TLS

True

ARIS_OAUTH_URL / ARIS_CLIENT_ID / ARIS_CLIENT_SECRET / ARIS_TENANT

OAuth2 client-credentials (preferred)

—

ARIS_TOKEN

static bearer token (alt to OAuth)

—

ARIS_USERNAME / ARIS_PASSWORD

HTTP basic (alt)

—

ARIS_PATHS_JSON

JSON overriding REST path templates per tenant

—

ARIS_ENABLE_WRITE

allow attribute writes

False

Tenant differences. ARIS deployments vary (Connect ABS portal vs the public ARIS API; on-prem vs Cloud). The defaults follow the common ARIS Connect ABS REST layout. If your tenant's paths differ, set ARIS_PATHS_JSON, e.g. {"models":"v2/repository/models","model_objects":"v2/models/{model_id}/objects"}.

MCP server / transport

Variable

Description

Default

TRANSPORT

stdio, streamable-http, or sse

stdio

HOST

Bind host (HTTP transports)

0.0.0.0

PORT

Bind port (HTTP transports)

8000

MCP_TOOL_MODE

Tool surface: condensed, verbose, or both

condensed

MCP_ENABLED_TOOLS / MCP_DISABLED_TOOLS

Comma-separated tool allow/deny list

—

MCP_ENABLED_TAGS / MCP_DISABLED_TAGS

Comma-separated tag allow/deny list

—

DEBUG

Verbose logging

False

PYTHONUNBUFFERED

Unbuffered stdout (recommended in containers)

1

Tool toggles

The action-routed tools can be disabled via their toggle env var (set to false): ARISTOOL (see the Available MCP Tools table above).

Telemetry & governance

Variable

Description

Default

ENABLE_OTEL

Enable OpenTelemetry export

True

OTEL_EXPORTER_OTLP_ENDPOINT

OTLP collector endpoint

—

OTEL_EXPORTER_OTLP_PUBLIC_KEY / OTEL_EXPORTER_OTLP_SECRET_KEY

OTLP auth keys

—

OTEL_EXPORTER_OTLP_PROTOCOL

OTLP protocol (e.g. http/protobuf)

—

EUNOMIA_TYPE

Authorization mode: none, embedded, remote

none

EUNOMIA_POLICY_FILE

Embedded policy file

mcp_policies.json

EUNOMIA_REMOTE_URL

Remote Eunomia server URL

—

Agent CLI (full [agent] runtime only)

Variable

Description

Default

MCP_URL

URL of the MCP server the agent connects to

http://localhost:8000/mcp

PROVIDER

LLM provider (e.g. openai)

openai

MODEL_ID

Model id (e.g. gpt-4o)

gpt-4o

ENABLE_WEB_UI

Serve the AG-UI web interface

True

Installation

Install the slim [mcp] extra. Install aris-mcp[mcp] — the MCP-server extra that pulls only the FastMCP / FastAPI tooling (agent-utilities[mcp]). It deliberately excludes the heavy agent runtime (the epistemic-graph engine, pydantic-ai, dspy, llama-index, tree-sitter), so uvx/container installs are dramatically smaller and faster. Use the full [agent] extra only when you need the integrated Pydantic AI agent.

Pick the extra that matches what you want to run:

Extra

Installs

Use when

aris-mcp[mcp]

Slim MCP server only (agent-utilities[mcp] — FastMCP/FastAPI)

You only run the MCP server (smallest install / image)

aris-mcp[agent]

Full agent runtime (agent-utilities[agent,logfire] — Pydantic AI + the epistemic-graph engine)

You run the integrated agent

aris-mcp[all]

Everything (mcp + agent + logfire)

Development / both surfaces

# MCP server only (recommended for tool hosting — slim deps)
uv pip install "aris-mcp[mcp]"

# Full agent runtime (Pydantic AI + epistemic-graph engine)
uv pip install "aris-mcp[agent]"

# Everything (development)
uv pip install "aris-mcp[all]"      # or: python -m pip install "aris-mcp[all]"

Container images (:mcp vs :agent)

One multi-stage docker/Dockerfile builds two right-sized images, selected by --target:

Image tag

Build target

Contents

Entrypoint

knucklessg1/aris-mcp:mcp

--target mcp

aris-mcp[mcp] — slim, no engine/pydantic-ai/dspy/llama-index/tree-sitter

aris-mcp

knucklessg1/aris-mcp:latest

--target agent (default)

aris-mcp[agent] — full agent runtime + epistemic-graph engine

aris-agent

docker build --target mcp   -t knucklessg1/aris-mcp:mcp    docker/   # slim MCP server
docker build --target agent -t knucklessg1/aris-mcp:latest docker/   # full agent

docker/mcp.compose.yml runs the slim :mcp server; docker/agent.compose.yml runs the agent (:latest) with a co-located :mcp sidecar.

Knowledge-graph database (epistemic-graph)

The full agent ([agent] / :latest) embeds the epistemic-graph engine (pulled in transitively via agent-utilities[agent]). For production — or to share one knowledge graph across multiple agents — run epistemic-graph as its own database container and point the agent at it instead of embedding it. Deployment recipes (single-node + Raft HA), connection config, and the full database architecture (with diagrams) are documented in the epistemic-graph deployment guide. The slim [mcp] server does not require the database.

Run

aris-mcp                       # stdio (default)
aris-mcp --transport streamable-http --host 0.0.0.0 --port 8000

Deployment

  1. stdio — uv run aris-mcp (see mcp_config.json).

  2. streamable-http — aris-mcp --transport streamable-http --port 8000.

  3. local container — build from docker/ and run with the env above.

  4. remote — point your client at http://aris-mcp.arpa/mcp.

Deploy with agent-os-genesis

This package can be provisioned for you — skill-guided — by the agent-os-genesis universal skill (its single-package deploy mode): it picks your install method, seeds secrets to OpenBao/Vault (or .env), trusts your enterprise CA, registers the MCP server, and verifies it — the same machinery that stands up the whole Agent OS, narrowed to just this package. Ask your agent to "deploy aris-mcp with agent-os-genesis".

Install mode

Command

Bare-metal, prod (PyPI)

uvx aris-mcp · or uv tool install aris-mcp

Bare-metal, dev (editable)

uv pip install -e ".[all]" · or pip install -e ".[all]"

Container, prod

deploy knucklessg1/aris-mcp:latest via docker-compose / swarm / podman / podman-compose / kubernetes

Container, dev (editable)

deploy docker/compose.dev.yml (source-mounted at /src; edits live on restart)

Secrets are read-existing + seeded via vault_sync — you are only prompted for what's missing.

This server cannot be installed

A
license - permissive license
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quality - not tested
A
maintenance

How are these scores calculated?

Maintenance

–Maintainers
–Response time
6dRelease cycle
2Releases (12mo)
Commit activity

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