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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
ARIS_TOKENNoStatic bearer token
ARIS_TENANTNoARIS tenant identifier
ARIS_API_BASENoARIS REST base URL (tenant API root)http://localhost/abs/api
ARIS_PASSWORDNoBasic auth password
ARIS_USERNAMENoBasic auth username
ARIS_CLIENT_IDNoOAuth2 client ID
ARIS_OAUTH_URLNoOAuth2 token URL
ARIS_SSL_VERIFYNoVerify TLSTrue
ARIS_ENABLE_WRITENoAllow attribute writesFalse
ARIS_CLIENT_SECRETNoOAuth2 client secret

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": true
}
logging
{}
prompts
{
  "listChanged": true
}
resources
{
  "subscribe": false,
  "listChanged": true
}

Tools

Functions exposed to the LLM to take actions

NameDescription
aris_ingest_modelsB

Natively ingest ARIS models into epistemic-graph as typed nodes.

Lists via the real ARIS client and pushes typed OWL nodes + links through the fast engine client. Best-effort: returns {"ingested": None} when no engine is reachable. CONCEPT:AU-KG.ingest.enterprise-source-extractor.

aris_ingest_model_exportB

Store a raw ARIS model export (bytes) as a content-addressed KG blob.

The export bytes are supplied base64-encoded (rendered/exported out-of-band by the caller), stored via MediaStore as a :Blob + :ModelExport node linked to its :ProcessModel. Best-effort no-op when no engine is reachable. CONCEPT:AU-KG.ingest.list-durable-media.

aris_get_modelB

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

aris_list_model_attributesB

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

aris_list_model_connectionsB

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

aris_list_model_objectsB

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

aris_list_modelsB

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

aris_set_model_attributesC

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

aris_set_object_attributesC

Write/update attributes on a single object.

Prompts

Interactive templates invoked by user choice

NameDescription
connector-statusAsk for this connector server's current operational status.

Resources

Contextual data attached and managed by the client

NameDescription
_connector_status_resourceNative resource exposing this server's static status payload.
ontology://aris-mcp/aris.ttl
connector-resourcesData sources, ontology mappings and resources of this connector.
aris-process-modeling/SKILL.mdRead Software AG ARIS process models over the aris-mcp MCP server — list the model inventory, fetch one model's metadata/attributes, and read its EPC objects (functions/events/rule operators) and directed control-flow connections. Use when the agent must inventory ARIS models, open one model by GUID, or inspect a model's EPC structure. Do NOT use for ingesting models into the knowledge graph (use aris-kg-ingestion) or for control-flow / bottleneck analysis of a whole repository (use aris-process-mining).
aris-process-modeling/_manifestFile listing for aris-process-modeling
aris-process-mining/SKILL.mdAnalyze the control flow of Software AG ARIS EPC models over the aris-mcp MCP server — trace event→function→event paths, find splits/joins at rule operators, spot disconnected or dead-end objects, and reason about a model's structure. Use when the agent must explain how a process flows, validate an EPC's connectedness, or compare paths through a model. Do NOT use to merely list/read models (use aris-process-modeling) or to ingest them into the knowledge graph (use aris-kg-ingestion).
aris-process-mining/_manifestFile listing for aris-process-mining
aris-kg-ingestion/SKILL.mdNatively ingest Software AG ARIS process models into the epistemic-graph knowledge graph over the aris-mcp MCP server — push models as typed :ProcessModel nodes, a single model's EPC objects as :EPCFunction/:EPCEvent/ :EPCRule with :flowsTo control-flow edges, and raw model exports as content-addressed :ModelExport (:MediaAsset) blobs. Use when the agent must mirror ARIS content into the KG for cross-source querying. Do NOT use to merely read models (use aris-process-modeling) or to analyze a single model's flow in place (use aris-process-mining).
aris-kg-ingestion/_manifestFile listing for aris-kg-ingestion
aris-mcp-development/SKILL.mdDevelop and maintain the Software AG ARIS connector while preserving its Connector boundary, REST client contract, authentication policy, KG source declarations, package contents, and release evidence.
aris-mcp-development/_manifestFile listing for aris-mcp-development

TDQS

B3.4/5.0

Scored across 9 tools

Disambiguation4/5

Most tools target distinct resource+action pairs (list models, list objects, list connections, set attributes), so selection is generally clear. However, aris_get_model (metadata including attributes) overlaps meaningfully with aris_list_model_attributes, and the two ingest tools (ingest_models vs ingest_model_export) require reading descriptions to distinguish bulk ingestion from blob storage.

Naming Consistency5/5

All tools use a consistent snake_case aris_ prefix followed by verb_noun patterns (aris_list_models, aris_get_model, aris_set_model_attributes). The convention is predictable throughout, with only minor stylistic variance in the longer ingest names.

Tool Count5/5

Nine tools is well-scoped for an ARIS-to-KG bridge: reads, writes, and ingestion paths each have a clear purpose. No tool appears redundant enough to remove, and nothing feels thin.

Completeness4/5

The surface covers listing models, inspecting metadata/attributes/objects/connections, writing model and object attributes, and both bulk and blob ingestion. Minor gaps exist: no get_object or object-level create/delete, no model delete, and no tenant/database listing, but core ingestion and writeback workflows are covered.

Maintenance

ActivityActive
ResponsivenessNo issues