Outlook MCP Server
MCP server that uses Microsoft Entra OAuth 2.0 On-Behalf-Of flow to access Microsoft Graph for Outlook data, enabling email, calendar, and contacts interactions via MCP tools.
README
Outlook MCP Server
This server uses Microsoft Entra's OAuth 2.0 On-Behalf-Of flow. The client application sends an access token issued for this MCP API; the server validates that token and exchanges it for a delegated Microsoft Graph access token.
Entra application contract
- Client application ID:
9b544eca-bd87-4849-b7fb-e96c944cdca8 - MCP/API application ID:
a7e86069-52f5-46b7-9a06-41d411c47410 - Tenant ID:
46c98d88-e344-4ed4-8496-4ed7712e255d - MCP delegated scope:
api://a7e86069-52f5-46b7-9a06-41d411c47410/access_as_user - OBO Graph scope:
https://graph.microsoft.com/.default
The bearer token sent to /mcp must be an access token for the MCP API, not
an ID token or a Graph access token. It must contain access_as_user in scp
and identify the client application in azp (v2 token) or appid (v1 token).
The MCP application registration must have delegated Microsoft Graph permissions with admin consent and a confidential-client credential. In Kubernetes, create the credential separately; never add its value to this repository:
kubectl create secret generic outlook-mcp-entra `
--namespace catalyst-prod `
--from-literal=client-secret='<secret-value>'
For local development, copy .env.example to .env, provide
ENTRA_CLIENT_SECRET, and export/load those variables before starting the
server. The production manifest reads the secret from outlook-mcp-entra.
A production-ready, forkable template for building MCP (Model Context Protocol) servers that deploy to the Catalyst Kubernetes platform.
This template uses the same proven SDK patterns running in production today (math-mcp-server, hsdes-mcp-server). Copy this folder, fill in your tools, and deploy in under 30 minutes.
Generated servers conform to the Intel IT MCP engineering standard (IT-MCP-STD-001): standardized naming, MCP-native tools tagged with annotations + governance _meta, risk tiers (R0-R3) with runtime enforcement of R2/R3 writes, data-freshness tags, and server-side telemetry (structured JSON logs with a correlation id and gateway-validated caller). A registry.yaml manifest records the server for the registry. (The deployed reference servers math-mcp-server and hsdes-mcp-server predate this convention.)
Prerequisites
Before using this template, make sure you have:
- Python 3.12+ installed locally
- Podman (for container builds) — setup guide
- kubectl configured with a Catalyst cluster kubeconfig
- Harbor access to push images to
amr-registry.caas.intel.com/catalyst/
See the full deployment guide for detailed prerequisites and access setup.
Quick Start
1. Copy the template
cp -r templates/mcp-server-template my-new-server
cd my-new-server
2. Find and replace all customization points
Search for >>> CUSTOMIZE across all files and replace the placeholders:
# See all customization points
grep -rn "CUSTOMIZE" .
At minimum, replace:
your-server-name→ your actual server name (e.g.,jira-mcp-server)API_BASE_URL→ the upstream REST API you're wrapping- Tool definitions in
server.py→ your actual tools
3. Define your tools
Edit server.py and replace the example tools (core.greeting.get, core.item.get, core.item.update) with your own. Tools are meaningful actions, not a 1:1 mirror of API endpoints — apply the test "would a user describe this action in natural language?".
- Add a
types.Tool(...)entry to theTOOLSlist with:nameas<domain>.<capability>.<verb_object>(the backing system never appears in a tool name)description+ JSON SchemainputSchemaannotations=types.ToolAnnotations(...)— mapside_effectsto hints:none/read=>readOnlyHint=True,write_irreversible=>destructiveHint=True,idempotentHintfromintel.it/idempotent_meta={...}Intel governance tags:risk_tier(R0-R3),side_effects,idempotent,data_classification, plus (for data tools)latency_class/answer_type/source_system
- Add a matching
case "<domain>.<capability>.<verb_object>":block incall_tool() - Use
_api_request()for upstream API calls,_ok()/_err()for responses - For R2 (reversible write) tools, require
reason,target_identifiers,idempotency_key; for R3 (irreversible) requirereason,target_identifiers,approval_id. The dispatcher enforces these before any upstream call and emits an AUDIT log - Update
registry.yamlso the registry record matches the server's tools
4. Test locally
python -m venv .venv
.venv\Scripts\activate # Windows
# source .venv/bin/activate # Linux/macOS
pip install -r requirements.txt
python server.py
Verify the server is running:
# Health check
curl http://localhost:8000/health
# List tools (MCP JSON-RPC)
curl -X POST http://localhost:8000/mcp/ ^
-H "Content-Type: application/json" ^
-H "Accept: application/json, text/event-stream" ^
-d "{\"jsonrpc\":\"2.0\",\"id\":1,\"method\":\"tools/list\",\"params\":{}}"
# Call the greeting tool
curl -X POST http://localhost:8000/mcp/ ^
-H "Content-Type: application/json" ^
-H "Accept: application/json, text/event-stream" ^
-d "{\"jsonrpc\":\"2.0\",\"id\":2,\"method\":\"tools/call\",\"params\":{\"name\":\"core.greeting.get\",\"arguments\":{\"name\":\"World\"}}}"
5. Build the container
podman build -t your-server-name:1.0.0 .
6. Push to Harbor registry
podman tag your-server-name:1.0.0 amr-registry.caas.intel.com/catalyst/your-server-name:1.0.0
podman push --tls-verify=false amr-registry.caas.intel.com/catalyst/your-server-name:1.0.0
7. Deploy to Kubernetes
# Set kubeconfig for your cluster
$env:KUBECONFIG = "path/to/kube-configs/amr-its-compute-cluster.yaml"
kubectl apply -f k8s-deploy.yaml
kubectl apply -f ingress.yaml
# Watch pod status
kubectl get pods -n catalyst -l app=your-server-name -w
8. Verify the deployment
curl https://api-suite-dev.catalyst.intel.com/your-server-name/health
Auth Patterns
No Auth (Default)
The template ships with no authentication — any client with network access can call your tools. This is appropriate for internal demo servers and tools that don't access sensitive APIs.
Bearer Token Passthrough
If your upstream API requires a user-provided Bearer token (e.g., Intel SSO id_token for HSDES, ServiceNow, etc.), enable the auth middleware:
- In
server.py: Uncomment theTokenExtractorASGIclass, theContextVar, and theget_bearer_token()helper function (clearly marked in the file) - In the ASGI wiring section: Swap the
Mountline to useTokenExtractorASGI:# Comment out this line: # Mount("/mcp", app=session_manager.handle_request), # Uncomment this line: Mount("/mcp", app=TokenExtractorASGI(session_manager.handle_request)), - In
_api_request(): Uncomment the token forwarding lines to attach the Bearer token to upstream requests
See servers/hsdes-mcp-server/ for a complete working example of this pattern.
VS Code MCP Client Configuration
No-auth server
Add to your .vscode/mcp.json or VS Code settings:
{
"servers": {
"your-server-name": {
"type": "http",
"url": "https://api-suite-dev.catalyst.intel.com/your-server-name/mcp/"
}
}
}
Auth server (Bearer token)
{
"servers": {
"your-server-name": {
"type": "http",
"url": "https://api-suite-dev.catalyst.intel.com/your-server-name/mcp/",
"headers": {
"Authorization": "Bearer ${input:your_server_token}"
}
}
},
"inputs": [
{
"id": "your_server_token",
"type": "promptString",
"description": "Bearer token (Intel SSO id_token) for your-server-name",
"password": true
}
]
}
File Overview
| File | Purpose |
|---|---|
server.py |
MCP server with tool definitions and ASGI wiring |
requirements.txt |
Python dependencies (pinned to tested versions) |
Dockerfile |
Multi-stage container build with non-root user |
k8s-deploy.yaml |
Kubernetes Deployment + Service |
ingress.yaml |
Traefik Ingress + Middleware for external HTTPS access |
registry.yaml |
IT-MCP-STD-001 registry manifest (server + tool metadata) |
.env.example |
Environment variable reference (copy to .env) |
.vscode/mcp.json |
VS Code MCP client configuration |
Full Documentation
For the complete deployment pipeline including Podman VM proxy setup, Harbor authentication, kubeconfig management, and troubleshooting:
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