Azure Databricks Jobs MCP Server
Exposes Azure Databricks Jobs tools (list, run, get output) with Entra ID authentication and OBO flow for per-user context.
README
Azure Databricks Jobs MCP Server
[!CAUTION] This is a sample implementation provided for educational purposes. It is not intended for production use without proper security review, testing, and hardening. Use at your own risk.
A Python MCP server that exposes a limited set of Azure Databricks Jobs capabilities. It authenticates callers with Microsoft Entra ID and uses the On-Behalf-Of (OBO) flow so that, when used from GitHub Copilot in VS Code (or any other client), every Databricks call is made as the signed-in user (their Databricks permissions apply).
Built with FastMCP and managed with uv.
Tools
| Tool | Databricks endpoint | Description |
|---|---|---|
list_jobs |
GET /api/2.2/jobs/list |
List jobs (helps discover job IDs). |
list_runs |
GET /api/2.2/jobs/runs/list |
List job runs, filter by job / state. |
get_run |
GET /api/2.2/jobs/runs/get |
Get details/status of a run. |
get_run_output |
GET /api/2.2/jobs/runs/get-output |
Get a task run's output. |
run_now |
POST /api/2.2/jobs/run-now |
Trigger a new run of a job. |
Only these jobs-related tools are exposed — no other Databricks capabilities.
How authentication works
This server is an OAuth 2.0 protected resource (RFC 9728). It does not run any login UI of its own — it validates the bearer tokens it receives and tells clients which authorization server (Entra) issues them.
VS Code Copilot --OAuth--> Microsoft Entra ID --token--> Copilot --Bearer--> MCP server --OBO--> Databricks
(user signs in directly) (issues access token) (validates JWT) (acts as user)
- Copilot reads this server's Protected Resource Metadata at
/.well-known/oauth-protected-resource/mcp(RFC 9728 §3.1 appends the/mcpresource path after/.well-known/oauth-protected-resource), which names Entra as the authorization server and the scope to request. - Copilot performs the OAuth flow directly with Entra and receives an access token
with audience = this app's API (
api://<client_id>). - Copilot calls the MCP endpoint with that token. The server validates the JWT locally against Entra's published JWKS (signature, issuer, audience, and required scope).
- Each tool takes the validated inbound token and runs the OBO exchange (MSAL) for
scope
2ff814a6-3304-4ab8-85cb-cd0e6f879c1d/.default(the Azure Databricks resource). - The resulting token is used as
Authorization: Beareragainst the Jobs API.
Server credential: client secret or managed identity
Token validation (step 3) needs no secret — the server only fetches Entra's public JWKS. The On-Behalf-Of exchange (step 4) is where the server acts as a confidential client and must prove the app's identity. There are two ways to do that:
- Client secret — set
AZURE_CLIENT_SECRET. Simplest for local development. - Managed identity (recommended on Azure) — set
AZURE_USE_MANAGED_IDENTITY=true. The app authenticates with a federated identity credential: a managed identity mints a short‑lived assertion for theapi://AzureADTokenExchangeaudience, which Entra trusts in place of a secret. No secret is stored or rotated. See Deploying to Azure Container Apps.
Why both an app registration and a managed identity? The managed identity replaces the client secret, not the app registration — they do different jobs:
- The app registration exposes the API/scopes and holds the delegated
user_impersonationpermission that makes the OBO ("act as the user") exchange possible. Managed identities can do none of these — they only get tokens for themselves (app-only), never on behalf of a user.- The managed identity is just a secretless way to prove the app registration's identity during the OBO exchange (via the federated credential).
So you can drop the secret, but not the app registration — unless you give up per-user access and call Databricks as a single shared service principal instead.
Prerequisites
- Python 3.12+ and uv
- An Azure Databricks workspace, and a user with access to it
- An Entra app registration (see below)
Entra app registration requirements
This server assumes the app registration already exists. Configure it as follows.
- Expose an API
- Application ID URI: keep the default
api://<client_id>. - Add a scope, e.g.
jobs(matchesMCP_REQUIRED_SCOPES).
- Application ID URI: keep the default
- Certificates & secrets → create a client secret (store it in
.env), or use a managed identity when deployed (see below). This credential is used only for the OBO exchange. - API permissions → add AzureDatabricks →
user_impersonation(Delegated), then Grant admin consent. This permission lets the OBO exchange succeed.
Client access to the API
Because clients authenticate directly with Entra (which has no Dynamic Client
Registration), the MCP client needs to be a client Entra recognizes and must be
allowed to request the api://<client_id>/jobs scope. In VS Code, Copilot performs
the Entra sign-in when you first use a tool and requests the scope advertised in the
Protected Resource Metadata. Ensure user (or admin) consent is granted for the client
to access this API's jobs scope in your tenant.
Setup
# 1. Install dependencies
uv sync
# 2. Create your local config
cp .env.example .env # then fill in the values
# 3. Run the server (Streamable HTTP)
uv run databricks-jobs-mcp
The server listens on http://127.0.0.1:8000/mcp by default.
Configuration (.env)
| Variable | Required | Description |
|---|---|---|
AZURE_TENANT_ID |
yes | Entra tenant (directory) ID. |
AZURE_CLIENT_ID |
yes | App registration (client) ID. |
AZURE_CLIENT_SECRET |
conditional | App registration client secret. Required unless AZURE_USE_MANAGED_IDENTITY=true. |
AZURE_USE_MANAGED_IDENTITY |
no (false) |
Authenticate the OBO exchange with a managed identity federated credential instead of a secret. |
AZURE_MANAGED_IDENTITY_CLIENT_ID |
no | Client ID of the user-assigned managed identity. Omit for the system-assigned identity. |
MCP_BASE_URL |
no (http://localhost:8000) |
Public base URL; published as the resource identifier in Protected Resource Metadata. On Azure Container Apps it is auto-derived by combining the injected CONTAINER_APP_NAME and CONTAINER_APP_ENV_DNS_SUFFIX when left unset. |
MCP_HOST |
no (127.0.0.1) |
Bind interface. |
MCP_PORT |
no (8000) |
Bind port. |
MCP_REQUIRED_SCOPES |
no (jobs) |
Exposed API scope name(s), comma separated. |
DATABRICKS_HOST |
yes | Workspace URL, e.g. https://adb-xxxx.azuredatabricks.net. |
DATABRICKS_API_VERSION |
no (2.2) |
Jobs API version (use 2.1 only if needed). |
LOG_LEVEL |
no (INFO) |
Logging verbosity (DEBUG, INFO, WARNING, ERROR). Set to DEBUG to log the exact reason a token is rejected (issuer/audience/scope mismatch, signature/JWKS failures). |
Secrets live only in .env (gitignored).
Using from VS Code Copilot
A repo-level .mcp.json is included:
{
"mcpServers": {
"databricks-jobs": { "type": "http", "url": "http://localhost:8000/mcp" }
}
}
Start the server (uv run databricks-jobs-mcp), then open the repo in VS Code with
Copilot. On first use of a tool, Copilot opens the Entra sign-in flow; afterwards the
jobs tools are available and run as you.
Container image
A Dockerfile is included. It builds a slim, multi-stage image with
uv, runs as a non-root user, and binds the HTTP
transport to 0.0.0.0:8000 (via MCP_HOST / MCP_PORT) so it works behind an
ingress.
# Build
docker build -t databricks-jobs-mcp:latest .
# Run locally (the container listens on 8000)
docker run --rm -p 8000:8000 --env-file .env databricks-jobs-mcp:latest
Deploying to Azure Container Apps
Requires the Azure CLI with the
containerappextension and Docker. Replace the placeholder values below.
The app authenticates to Entra with a managed identity — no client secret is stored or rotated. It uses a federated identity credential (FIC): a user-assigned managed identity mints a short-lived assertion that Entra trusts in place of a secret.
# 0. Variables
RG=rg-databricks-mcp
LOCATION=swedencentral
ACR=acrdatabricksmcp... # must be globally unique
ENV=cae-databricks-mcp
APP=databricks-jobs-mcp
UAMI=id-databricks-mcp
CLIENT_ID=<client-id> # App REGISTRATION client ID (= AZURE_CLIENT_ID), NOT the managed identity
TENANT_ID=<tenant-id> # Entra tenant (directory) ID
# 1. Resource group + container registry
az group create -n $RG -l $LOCATION
az acr create -n $ACR -g $RG --sku Basic
# 2. Build & push the image (uses the included Dockerfile)
az acr build -r $ACR -t $APP:latest .
# 3. Container Apps environment
az containerapp env create -n $ENV -g $RG -l $LOCATION
# 4. Create a user-assigned managed identity and read its IDs
az identity create -n $UAMI -g $RG -l $LOCATION
MI_CLIENT_ID=$(az identity show -n $UAMI -g $RG --query clientId -o tsv)
MI_PRINCIPAL_ID=$(az identity show -n $UAMI -g $RG --query principalId -o tsv)
MI_RESOURCE_ID=$(az identity show -n $UAMI -g $RG --query id -o tsv)
# Let the managed identity pull images from the registry (no ACR admin user)
az role assignment create \
--assignee-object-id $MI_PRINCIPAL_ID --assignee-principal-type ServicePrincipal \
--role AcrPull \
--scope $(az acr show -n $ACR -g $RG --query id -o tsv)
# 5. Configure the app registration to trust the managed identity (FIC).
# --id is the app REGISTRATION (= AZURE_CLIENT_ID); the subject is the
# managed identity's principal ID, and the audience is fixed.
az ad app federated-credential create \
--id $CLIENT_ID \
--parameters '{
"name": "databricks-mcp-mi",
"issuer": "https://login.microsoftonline.com/'$TENANT_ID'/v2.0",
"subject": "'$MI_PRINCIPAL_ID'",
"audiences": ["api://AzureADTokenExchange"]
}'
# 6. Deploy the app with the managed identity assigned (no client secret)
az containerapp create \
-n $APP -g $RG --environment $ENV \
--image $ACR.azurecr.io/$APP:latest \
--registry-server $ACR.azurecr.io \
--registry-identity $MI_RESOURCE_ID \
--target-port 8000 --ingress external \
--min-replicas 1 \
--user-assigned $MI_RESOURCE_ID \
--env-vars \
AZURE_TENANT_ID=$TENANT_ID \
AZURE_CLIENT_ID=$CLIENT_ID \
AZURE_USE_MANAGED_IDENTITY=true \
AZURE_MANAGED_IDENTITY_CLIENT_ID=$MI_CLIENT_ID \
DATABRICKS_HOST=https://adb-xxxx.azuredatabricks.net
# 7. Fetch the app's FQDN
az containerapp show -n $APP -g $RG --query properties.configuration.ingress.fqdn -o tsv
The same, in PowerShell:
# 0. Variables
$RG = "rg-databricks-mcp"
$LOCATION = "swedencentral"
$ACR = "acrdatabricksmcp..." # must be globally unique
$ENVNAME = "cae-databricks-mcp"
$APP = "databricks-jobs-mcp"
$UAMI = "id-databricks-mcp"
$TENANT_ID = "<tenant-id>" # Entra tenant (directory) ID
$CLIENT_ID = "<client-id>" # App REGISTRATION client ID (= AZURE_CLIENT_ID), NOT the managed identity
# 1. Resource group + container registry
az group create -n $RG -l $LOCATION
az acr create -n $ACR -g $RG --sku Basic
# 2. Build & push the image (uses the included Dockerfile)
az acr build -r $ACR -t "$($APP):latest" .
# 3. Container Apps environment
az containerapp env create -n $ENVNAME -g $RG -l $LOCATION
# 4. Create a user-assigned managed identity and read its IDs
az identity create -n $UAMI -g $RG -l $LOCATION
$MI_CLIENT_ID = az identity show -n $UAMI -g $RG --query clientId -o tsv
$MI_PRINCIPAL_ID = az identity show -n $UAMI -g $RG --query principalId -o tsv
$MI_RESOURCE_ID = az identity show -n $UAMI -g $RG --query id -o tsv
$ACR_ID = az acr show -n $ACR -g $RG --query id -o tsv
# Let the managed identity pull images from the registry (no ACR admin user)
az role assignment create `
--assignee-object-id $MI_PRINCIPAL_ID --assignee-principal-type ServicePrincipal `
--role AcrPull `
--scope $ACR_ID
# 5. Configure the app registration to trust the managed identity (FIC).
# The audience is fixed; the subject is the managed identity's principal ID.
@{
name = "databricks-mcp-mi"
issuer = "https://login.microsoftonline.com/$TENANT_ID/v2.0"
subject = $MI_PRINCIPAL_ID
audiences = @("api://AzureADTokenExchange")
} | ConvertTo-Json | Set-Content -Path fic.json -Encoding utf8
az ad app federated-credential create --id $CLIENT_ID --parameters '@fic.json'
# 6. Deploy the app with the managed identity assigned (no client secret)
az containerapp create `
-n $APP -g $RG --environment $ENVNAME `
--image "$($ACR).azurecr.io/$($APP):latest" `
--registry-server "$($ACR).azurecr.io" `
--registry-identity $MI_RESOURCE_ID `
--target-port 8000 --ingress external `
--min-replicas 1 `
--user-assigned $MI_RESOURCE_ID `
--env-vars `
AZURE_TENANT_ID=$TENANT_ID `
AZURE_CLIENT_ID=$CLIENT_ID `
AZURE_USE_MANAGED_IDENTITY=true `
AZURE_MANAGED_IDENTITY_CLIENT_ID=$MI_CLIENT_ID `
DATABRICKS_HOST=https://adb-xxxx.azuredatabricks.net
# 7. Fetch the app's FQDN
az containerapp show -n $APP -g $RG --query properties.configuration.ingress.fqdn -o tsv
The app's public FQDN is shown after containerapp create (or via
az containerapp show -n $APP -g $RG --query properties.configuration.ingress.fqdn -o tsv).
After deploying:
MCP_BASE_URLis auto-derived from the stable Container Apps FQDN (CONTAINER_APP_NAME+CONTAINER_APP_ENV_DNS_SUFFIX), so you don't need to set it. (To override the URL, e.g. a custom domain, setMCP_BASE_URLexplicitly.)- No
AZURE_CLIENT_SECRETis needed. The OBO exchange uses the FIC instead. AZURE_MANAGED_IDENTITY_CLIENT_IDselects the user-assigned identity. Omit it only if you use the Container App's system-assigned identity (and set the FIC subject to that identity's principal ID instead).- Token validation is stateless, so the app scales to multiple replicas without extra configuration.
- The app registration still needs the AzureDatabricks →
user_impersonationpermission, which powers the OBO exchange. https://databricks-jobs-mcp.abcdef123456.swedencentral.azurecontainerapps.io/.well-known/oauth-protected-resource/mcpis the Protected Resource Metadata endpoint (RFC 9728). Copilot uses it to learn this server's resource identifier, the authorization server (Entra) to obtain tokens from, and the scope to request.
Here is an example of the metadata document returned by the deployed server:
{
"resource": "https://databricks-jobs-mcp.abcdef123456.swedencentral.azurecontainerapps.io/mcp",
"authorization_servers": [
"https://login.microsoftonline.com/<tenant-id>/v2.0"
],
"scopes_supported": [
"api://<client-id>/jobs"
],
"bearer_methods_supported": [
"header"
],
"resource_name": "Azure Databricks Jobs"
}
To use that in Copilot, you can use the following .mcp.json:
{
"mcpServers": {
"databricks-jobs-azure": {
"type": "http",
"url": "https://databricks-jobs-mcp.abcdef123456.swedencentral.azurecontainerapps.io/mcp"
}
}
}
Notes
- Inspired by the (stdio-based) databricks-solutions/ai-dev-kit; this server is intentionally HTTP + OBO and jobs-only.
Troubleshooting authentication (401 invalid_token)
A 401 Unauthorized with {"error": "invalid_token"} means the server rejected the
bearer token during JWT validation (signature, issuer, audience or required scope) —
it never reached a tool, so the OBO exchange is not involved yet. By default the logs
only show the generic Auth error returned: invalid_token. Set LOG_LEVEL=DEBUG
to make FastMCP's JWTVerifier log the precise reason:
- Issuer / audience / scope mismatch is logged at
WARNING, e.g.Bearer token rejected ... audience mismatch (got ..., expected ...). - Signature / JWKS / format failures are logged at
DEBUG, e.g.Token validation failed: JWT signature/format invalid.
When a token is rejected, the server also logs (at DEBUG) a decoded — but
unverified — summary of the offending token so you can see the actual claims
without capturing the bearer token by hand:
Rejected bearer token: header={alg=..., kid=..., typ=..., nonce=...} \
claims={iss=..., aud=..., appid/azp=..., ver=..., scp=..., exp=...}
The server also logs (at DEBUG) the exact values it validates against at startup:
Auth config: base_url=... issuer=... audiences=[...] required_scopes=[...] jwks_uri=...
JWT signature/format invalidwith a successful JWKS fetch? The token reached signature verification but failed. TheRejected bearer token:line tells you why:
nonce=PRESENT→ the client obtained a nonce-protected Microsoft token (issued when the token'saudis a Microsoft first-party resource, not this API). These are intentionally not validatable by third parties. The client must request a token for this API (api://<client_id>/jobs), as advertised in the Protected Resource Metadata — not for Microsoft Graph or another resource.not a well-formed JWS→ the client sent an opaque/garbled token, not a JWT.
Enable it on the deployed Container App (this restarts the revision):
az containerapp update -n $APP -g $RG --set-env-vars LOG_LEVEL=DEBUG
# then stream the logs and reproduce from Foundry
az containerapp logs show -n $APP -g $RG --follow
Common causes when calling from Microsoft Foundry:
- Audience mismatch — Foundry obtained a token whose
audis not this app (api://<client_id>/<client_id>). The metadata at/.well-known/oauth-protected-resource/mcpmust advertise this server's resource and theapi://<client_id>/jobsscope so the client requests a token for this API. - Issuer mismatch — the token must be a v2.0 token
(
https://login.microsoftonline.com/<tenant-id>/v2.0). - Missing scope — the token lacks the required
jobsscope (MCP_REQUIRED_SCOPES). - Wrong base URL — if
MCP_BASE_URLdoes not match the public FQDN, clients may request a token for the wrong resource. On Container Apps it is auto-derived; override only for custom domains.
Turn it back off once diagnosed:
az containerapp update -n $APP -g $RG --set-env-vars LOG_LEVEL=INFO
Example responses
Copilot summarizing a failed job run (list_runs / get_run):

Copilot explaining why the run failed (get_run_output):

Foundry showing the job run output in a notebook (get_run_output):

Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.