dss-mcp-bridge

Operate Dataiku DSS from any MCP client — Claude Code, Codex CLI, Cursor — over Streamable HTTP.

It is read-only by default, authenticates with bearer tokens, validates Origin and Host per the MCP specification, and records every tool call. What it exposes is a deliberate configuration choice, not an accident of what happens to be implemented.

Quick start

Not on PyPI yet — install from the repository:

git clone https://github.com/qsun-aidata/dss-mcp-bridge
cd dss-mcp-bridge
uv sync                                          # or: pip install .

cp .env.example .env && chmod 600 .env           # set DSS_MCP_DSS_API_KEY
uv run dss-mcp-bridge check                      # validate config + reach DSS
uv run dss-mcp-bridge serve                      # listens on 127.0.0.1:58000/mcp

Then connect your agent — the server prints the exact snippet for each one:

uv run dss-mcp-bridge client-config claude-code  # or codex | cursor | inspector

Related MCP server: LLM Wiki Streamable HTTP MCP Server

Connecting an agent

claude mcp add --transport http dataiku http://127.0.0.1:58000/mcp \
  --header "Authorization: Bearer $DSS_MCP_TOKEN"

Or in .mcp.json (project scope, shared with your team — the token stays in the environment):

{
  "mcpServers": {
    "dataiku": {
      "type": "http",
      "url": "http://127.0.0.1:58000/mcp",
      "headers": { "Authorization": "Bearer ${DSS_MCP_TOKEN}" }
    }
  }
}

Verify with /mcp.

In ~/.codex/config.toml:

[mcp_servers.dataiku]
url = "http://127.0.0.1:58000/mcp"
bearer_token_env_var = "DSS_MCP_TOKEN"

Codex reads the variable at connect time, so the token never lands in the config file.

In ~/.cursor/mcp.json (global) or .cursor/mcp.json (project):

{
  "mcpServers": {
    "dataiku": {
      "url": "http://127.0.0.1:58000/mcp",
      "headers": { "Authorization": "Bearer ${env:DSS_MCP_TOKEN}" }
    }
  }
}

Clients that support OAuth discovery find the server through the RFC 9728 metadata it publishes at /.well-known/oauth-protected-resource/mcp.

Permission tiers

DSS_MCP_MODE decides which tools exist. A tool above the active tier is never registered, so it does not appear in tools/list and a model cannot try to call it.

list_dku_tools reports the active mode, everything being withheld, and why — so an agent can explain the limitation instead of guessing.

Tools

search_dataset streams rows over the REST API with a scan cap; text_query matches any string column and filters add per-column conditions combined with AND.

dku_call reaches arbitrary methods of the dataikuapi surface. It ships disabled. DSS_MCP_DKU_CALL=allowlist permits only the read-only names in dku_call_allowlist.yaml; full removes that restriction and additionally requires DSS_MCP_MODE=admin. In every mode, attributes whose name starts with _ are refused, so dunder traversal is never reachable, and the allowlist gates the accessors used to serialize a result as well as the method you name.

The shipped allowlist covers project and dataset analysis. Instance administration — connections, users, groups, plugin presets — is left out on purpose, because allowlist mode registers dku_call at the read tier. Copy the file and point DSS_MCP_DKU_CALL_ALLOWLIST_FILE at your copy to widen it.

DSS Agent tools

Set DSS_MCP_AGENT_TOOLS=PROJECT_KEY:TOOL_ID,… and each one is registered as an MCP tool with a validated schema built from its DSS descriptor. A descriptor that cannot be loaded, or declares a parameter name Python cannot use, is reported in list_dku_tools rather than silently dropped.

Optional: in-process dataiku

The DSS REST API cannot write dataset rows, so write_dataset_records needs the in-process dataiku package — which ships with the DSS distribution, not PyPI. Run the bridge on a host that has it and put the DSS python directory on PYTHONPATH:

PYTHONPATH=/opt/dataiku-dss/dataiku-dss-14.7.3/python dss-mcp-bridge serve

Everything else works over REST from any host that can reach DSS_URL. When dataiku is missing, the affected tools are withheld and list_dku_tools says so.

Configuration

Full list with comments in .env.example; dss-mcp-bridge print-config shows the effective values with secrets redacted. The essentials:

The original script's names (DSS_URL, MCP_PORT, MCP_ACCESS_TOKEN, …) still work and log a deprecation warning. They will be removed in 1.0.

Deployment

Docker

docker build -t dss-mcp-bridge .
docker run --rm -p 58000:58000 --env-file .env \
  -e DSS_MCP_HOST=0.0.0.0 \
  -e DSS_MCP_PUBLIC_URL=http://localhost:58000/mcp \
  dss-mcp-bridge

systemd (user unit)

uv sync
cp .env.example .env && chmod 600 .env
./scripts/install-service.sh
journalctl --user -u dss-mcp-bridge -f

Remote DSS, local agent

The recommended layout is the bridge on the DSS host bound to loopback, reached through an SSH tunnel — no open port, no LAN exposure, and 127.0.0.1 stays a valid Host:

ssh -N -L 58000:127.0.0.1:58000 you@dss-host

To expose the port directly instead, set DSS_MCP_TOKEN (the server refuses to bind a non-loopback address without one) and DSS_MCP_PUBLIC_URL, and terminate TLS in front.

Security

Full model in docs/security.md; SECURITY.md covers reporting. In short:

• MCP endpoint access ≈ the privileges of DSS_MCP_DSS_API_KEY. Treat the endpoint as you would that key.

• Loopback bind by default; binding anything else without a token is refused at startup.

• Bearer tokens are compared as SHA-256 digests in constant time, are never logged, and can be rotated (several at once) while staying individually attributable in the audit log.

• Origin and Host are validated on every request (403 / 421), as the MCP spec requires.

• export_project cannot write outside DSS_MCP_EXPORT_DIR; upload_file rejects path-like names.

• The DSS API key and bearer tokens are scrubbed from errors, logs and audit records.

Verify a running deployment:

./scripts/smoke.sh http://127.0.0.1:58000/mcp "$DSS_MCP_TOKEN"

Development

uv sync --all-extras
uv run pytest              # tests + coverage gate
uv run ruff format --check src tests scripts
uv run ruff check src tests scripts
uv run mypy
python scripts/gen_tool_table.py --check   # README table matches the code

Related projects

Author

Qian SUN — contact@qsun.fr

Licensed under Apache License 2.0.