How do I use Canon MCP?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Canon MCP List all available domains in the context repository." That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

Canon MCP

by Jonvoge

Overview Schema Related Servers Score Discussions

Python

Hybrid

Canon MCP

The serving layer for Canon governed context repositories. Reads a canon-context-accelerator repo at runtime and exposes its domain knowledge to AI agents over the MCP protocol, executing DAX and SQL queries under the user's identity via Entra OBO.

canon-context-accelerator (context layer)
  domains/<slug>/*.yaml,*.md   ──git read (60s TTL)──►  canon-mcp (this repo)
  _compiled/_index.json                                   single container
  _compiled/bundles/<domain>.md                           6 MCP tools
  .canon-cache/<d>/<connector_id>/schema.json             OBO → Fabric

Architecture invariant: the image carries code, not content. Anything a serving path reads must be readable from git at runtime. Content changes are a push, not a redeploy.

Tools

Tool	Description
`list_domains`	List all Canon domains from the compiled index
`get_domain_context`	Full grounding bundle for a domain (call before any query)
`query_measures`	Compose and execute SUMMARIZECOLUMNS DAX server-side (governed)
`run_dax`	Raw DAX escape hatch — requires justification, logged
`execute_sql`	Governed SQL fallback against warehouse connectors
`whoami`	Diagnostics: UPN, OBO health, config completeness

Related MCP server: Volterra Knowledge Engine

Environment variables

Repo pointer (required for remote mode)

Variable	Description
`CANON_REPO_PROVIDER`	`github` or `ado` — enables remote git reads; omit for local file mode
`CANON_REPO_OWNER`	GitHub org / ADO org
`CANON_REPO_NAME`	Repository name
`CANON_REPO_TOKEN`	PAT with read:contents scope
`CANON_REPO_BRANCH`	Branch to read from (default: `main`)
`CANON_REPO_ADO_ORG`	ADO org name (ADO only)
`CANON_REPO_ADO_PROJECT`	ADO project name (ADO only)

Auth (required for HTTP mode)

Variable	Description
`CANON_AUTH_TENANT_ID`	Entra tenant ID
`CANON_AUTH_CLIENT_ID`	App registration client ID
`CANON_AUTH_CLIENT_SECRET`	Client secret (for OBO token acquisition)
`CANON_MCP_BASE_URL`	Public HTTPS URL of this server (used in OAuth metadata)

Transport / runtime

Variable	Description
`CANON_MCP_PORT`	HTTP port (default: `8000`)
`CANON_MCP_TRANSPORT`	`streamable-http` (default) or `stdio`
`CANON_REPO_ROOT`	Local path to context repo (local/stdio mode only)

Env vars carry secrets and repo-pointer config only — never topology. Workspace IDs, dataset IDs, and connector topology come from scan-config.yaml in the context repo, not from environment variables.

Local / stdio mode

CANON_REPO_ROOT=/path/to/canon-context-accelerator \
CANON_MCP_TRANSPORT=stdio \
uv run python -m serving.mcp.server

HTTP / Container App mode

CANON_REPO_PROVIDER=github \
CANON_REPO_OWNER=YourOrg \
CANON_REPO_NAME=canon-context-accelerator \
CANON_REPO_TOKEN=ghp_... \
CANON_AUTH_TENANT_ID=... \
CANON_AUTH_CLIENT_ID=... \
CANON_AUTH_CLIENT_SECRET=... \
CANON_MCP_BASE_URL=https://your-container-app.azurecontainerapps.io \
uv run python -m serving.mcp.server

Development

uv sync --extra dev
uv run pytest
uv run ruff check .

CI runs ruff check + pytest on every PR via .github/workflows/test.yml.

Two-repo contract

canon-mcp consumes these artifacts from the context repo (never baked into the image):

Artifact	Produced by	Used for
`_compiled/_index.json`	`compile.yml`	`list_domains`, domain enum
`_compiled/bundles/<domain>.md`	`compile.yml`	`get_domain_context`
`domains/<d>/models/<m>.yaml`	humans + scan	`query_measures` validation
`domains/<d>/examples.yaml`	humans	few-shot grounding in bundle
`connections/<c>.yaml`	humans	`execute_sql` allow-list
`scan-config.yaml` → `domains[].models[]`, `connectors[]`	humans	connector resolution
`.canon-cache/<d>/<connector_id>/{schema,profiles}.json`	`scan.yml`	model schema, dim profiles

Changing any of these shapes is a coordinated two-repo migration.

This server cannot be installed

license - permissive license

quality - not tested

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

–Release cycle

–Releases (12mo)

Commit activity

Resources

GitHub Repository

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