Agentic CRM — Odoo + Microsoft Foundry

From CRM insight to autonomous action. A working demo showing an AI agent read live CRM data, reason across multiple signals, and take approved actions — built on a self-hosted Odoo backend and a pro-code agent on Microsoft Foundry.

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What this is

Most "agentic CRM" demos are either a chatbot bolted onto static screenshots, or a low-code assistant that can't explain its own reasoning. This project is neither: it's a real Odoo CRM instance, seeded with a coherent fictional dataset, exposed to a hosted Foundry agent through a custom-built MCP server — so every answer the agent gives is grounded in an actual queryable record, not a hallucinated summary.

The fictional premise: Meridian Fleet Technologies sells fleet telematics, cold-chain monitoring, and supply-chain SaaS/hardware to logistics, retail-distribution, and manufacturing customers. Every account, product, and support case in the demo dataset is written to be plausible within that business.

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Architecture

flowchart LR
    A[Foundry Agent] -->|MCP tool calls over HTTPS| B[Cloudflare Tunnel]
    B --> C[MCP Server<br/>Python / FastMCP]
    C -->|XML-RPC| D[(Odoo CRM<br/>+ PostgreSQL)]

• Odoo CRM — the business system of record. Self-hosted Community Edition via Docker, chosen deliberately over SaaS trials to keep unrestricted External API access.
• MCP server — a Python service that translates Model Context Protocol tool calls into Odoo XML-RPC calls, and back into readable results. Runs on Streamable HTTP so a hosted agent can call it directly.
• Cloudflare Tunnel — exposes the local MCP server over a public HTTPS URL without opening any inbound ports.
• Microsoft Foundry Agent Service — hosts the actual agent: grounds responses in CRM context, calls the MCP tools, and enforces human approval before any write action.

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Tech stack

Layer	Technology
CRM backend	Odoo 19 Community, PostgreSQL 16, Docker Compose
Data/tool layer	Custom MCP server (Python, FastMCP SDK) over Odoo's XML-RPC API
Tunneling	Cloudflare Tunnel (cloudflared)
Agent layer	Microsoft Foundry Agent Service — hosted agent
Cases model	Odoo Project app (Community-compatible substitute for the Enterprise-only Helpdesk app)

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Agent scenarios

Scenario	Question it answers	Key tool(s)
Sales Pipeline Agent	"Which deals are likely to slip this month?"	find_stalled_opportunities, create_followup_task
Customer Risk Agent	"Which customers need attention today? Why?"	list_accounts_needing_attention, explain_account_risk, escalate_case
Meeting Prep Agent	"Prepare me for my call with this account."	prepare_meeting_brief
Executive Reporting Agent	"Give me this week's customer and pipeline health."	get_weekly_executive_summary

Two tools (create_followup_task, escalate_case) write to Odoo. Every other tool is read-only. Write actions are designed to be gated behind explicit human approval in the agent's instructions — the agent explains and recommends first, and only acts once approved.

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Repository structure

.
├── docker-compose.yml               # Odoo + PostgreSQL services
├── addons/                          # Odoo custom addons mount point
├── seed_demo_data.py                # Seeds Odoo with the demo dataset
├── odoo_mcp_foundry_connector.py    # MCP server exposing 7 tools over XML-RPC (the one Foundry connects to)
├── testing-connection.py            # Standalone XML-RPC auth sanity check
├── .env.example                     # Template for required environment variables — copy to .env, never commit .env
├── .gitignore
├── pyproject.toml / uv.lock         # Python dependency management (uv)
├── .python-version
├── command.md                       # Command reference
├── restore_database.md              # Snapshot/restore instructions
├── Tunnel-cheat-sheet.md            # Full command-by-command tunnel reference
└── README.md

Note: this repo previously carried two other MCP server drafts (mcp-server.py, odoo-mcp-server.py) from earlier iterations. Only odoo_mcp_foundry_connector.py is live — the other two should be deleted before this goes public, since leftover near-duplicate files read as unfinished work to anyone reviewing the repo. backup.dump and hero_reference.json are environment-specific/generated output and should not be tracked in git — see Security below.

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Getting started

Three processes need to run at once: Odoo, the MCP server, and a tunnel.

1. Start Odoo

docker compose up -d

Then install the CRM, Contacts, Project, and Sales apps from the Odoo Apps screen.

2. Seed the demo data

python seed_demo_data.py

Creates 20 products, 6 hand-crafted "hero" accounts (each engineered to demonstrate one scenario above), and ~44 additional accounts with contacts, opportunities, activities, and cases. Record IDs for the hero accounts are saved to hero_reference.json.

3. Run the MCP server

export ODOO_URL="http://localhost:8069"
export ODOO_DB="your-db-name"
export ODOO_USERNAME="agent@demo.local"
export ODOO_PASSWORD="your-agent-password"
export MCP_HOST="0.0.0.0"
export MCP_PORT="8000"

uv run python odoo_mcp_foundry_connector.py --http

Use a dedicated least-privilege Odoo user for ODOO_USERNAME — not the admin account.

4. Expose it and connect Foundry

cloudflared tunnel --url http://localhost:8000

Register the printed URL (with /mcp appended) as an MCP Toolbox in your Foundry project.

For a full command-by-command reference, see Tunnel-cheat-sheet.md. For database snapshot/restore, see restore_database.md.

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Demo flow

1. Open the Odoo CRM dashboard — signals come from a real business app.
2. Ask the agent: "Which accounts need attention today?" — retrieval and prioritization over live records.
3. Ask: "Why is this account risky?" — multi-factor reasoning across opportunities, cases, and activity history.
4. Ask: "Draft a follow-up email." — content generation grounded in account context.
5. Approve task creation — human-in-the-loop write action.
6. Trigger an escalation — event-driven automation path.

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Security

This repo previously had real credentials exposed in tracked files — if you're forking or referencing this project, note the pattern below rather than the mistake:

• Never commit .env. All credentials are read from environment variables (ODOO_URL, ODOO_DB, ODOO_USERNAME, ODOO_PASSWORD) — see .env.example for the required keys. Both scripts refuse to run with a clear error if required variables are missing, rather than falling back to a hardcoded default.
• hero_reference.json and backup.dump are environment-specific generated output, not source code — they're gitignored and should never be tracked. If either is currently committed in your history, remove them with git rm --cached hero_reference.json backup.dump and commit that removal.
• If credentials were ever committed and pushed (even briefly, even in an old commit), rotate them immediately in Odoo — deleting the file afterward does not remove it from git history. Scrubbing history (git filter-repo or the BFG Repo-Cleaner) is the correct fix if the repo needs to stay public and keep its commit history; for a solo demo repo, deleting and recreating it clean is often simpler.
• Least privilege: the MCP server authenticates as a scoped demo Odoo user (agent@demo.local in this project), not admin — see Odoo_Setup_and_Demo_Data_Guide for how that user was created with restricted access rights.
• Fictional data only — no real customer or personal information anywhere in the dataset.
• Read/write separation — 5 of the 7 MCP tools are strictly read-only; the two write tools (create_followup_task, escalate_case) are designed to sit behind explicit human approval in the agent's instructions, not to be called freely.

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Status

Phase	Status
Odoo CRM foundation + demo data	✅ Complete
MCP server + tunnel exposure	✅ Complete
Foundry agent creation	✅ Complete
Automation (scheduled runs, notifications)	⬜ Planned
Observability & demo polish	⬜ Planned

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License

This is a demo/portfolio project using entirely fictional data. Not affiliated with or endorsed by Odoo S.A. or Microsoft.