Langbridge

Langbridge is an open source, self-hostable analytics runtime for structured data workloads, built for agentic analytics applications. It provides a unified runtime for connecting to data sources, defining semantic models, executing federated queries, and orchestrating agent-style analytical workflows. The runtime is accessible through a Python SDK and a documented HTTP API, and it can optionally serve a lightweight UI and mount an MCP endpoint.

What You Get

• A runtime host for executing agentic analytics workloads, with support for data source connectors, semantic modeling, federated query planning and execution, and agent orchestration.
• A Python SDK for interacting with the runtime, including tools for defining connectors, semantic models, and agents.
• A built-in UI for visualizing and interacting with runtime execution.
• An MCP endpoint for integrating with external agentic systems.

Repository Layout

The repository is organized into the following key areas:

• langbridge/: core runtime host implementation, including API, execution engine, connector framework, and MCP endpoint
• langbridge-connectors/: collection of pre-built connectors for common data sources and services (e.g. Shopify, Salesforce, Stripe, etc.)
• apps/runtime-ui/: React source for the runtime UI
• packages/sdk/: packaging for the standalone SDK distribution
• examples/: runnable host and SDK examples
• docs/: architecture, deployment, and development docs

Quick Start

Create an environment and install the runtime:

python -m venv .venv
source .venv/bin/activate
pip install -r requirements/dev.txt
pip install -e .

The dev requirements also include packaging tools for release work. To build the runtime package locally:

python -m build --no-isolation

Seed the local demo data:

python examples/sdk/semantic_query/setup.py

Start the runtime host:

langbridge serve --config examples/deployment/runtime_host/langbridge_config.yml --host 127.0.0.1 --port 8000

Apply runtime metadata migrations explicitly when you need a controlled rollout:

langbridge migrate --config examples/deployment/runtime_host/langbridge_config.yml

Open the runtime API docs at http://127.0.0.1:8000/api/runtime/docs.

Enable the runtime UI:

langbridge serve --config examples/deployment/runtime_host/langbridge_config.yml --features ui

Enable the MCP endpoint:

langbridge serve --config examples/deployment/runtime_host/langbridge_config.yml --features mcp

Enable the BI / ODBC endpoint:

langbridge serve --config examples/deployment/runtime_host/langbridge_config.yml --features odbc --odbc-port 15432

Enable both:

langbridge serve --config examples/deployment/runtime_host/langbridge_config.yml --features ui,mcp

You can also combine all runtime-facing surfaces:

langbridge serve --config examples/deployment/runtime_host/langbridge_config.yml --features ui,mcp,odbc --odbc-port 15432

SQLite metadata stores auto-apply Alembic migrations by default on startup. For managed/self-hosted production deployments, switch runtime.metadata_store to Postgres, run langbridge migrate --config ..., and set runtime.migrations.auto_apply: false if you want startup to fail until the DB is upgraded explicitly.

Runtime UI

The runtime UI is source-controlled in apps/runtime_ui_next and built into langbridge/ui/static, which the Python host serves when ui is enabled. The legacy apps/runtime_ui app remains in the repo for rollback/reference during migration.

For local UI development:

langbridge serve --config examples/deployment/runtime_host/langbridge_config.yml --features ui
cd apps/runtime_ui_next
npm install
npm run dev

To build the production UI bundle:

cd apps/runtime_ui_next
npm install
npm run build

Packaging And CodeArtifact

Build both Python distributions from the repo root:

make build

Build only the runtime package:

make build-runtime

Build only the SDK package:

make build-sdk

Publish the runtime package to AWS CodeArtifact with GNU Make after configuring an IAM user or role that can call codeartifact:GetAuthorizationToken, codeartifact:PublishPackageVersion, and sts:GetServiceBearerToken. The aws CLI command must already be installed on your machine:

make publish-codeartifact \
  CODEARTIFACT_DOMAIN=langbridge \
  CODEARTIFACT_DOMAIN_OWNER=060795918689 \
  CODEARTIFACT_REPOSITORY=langbridge \
  AWS_REGION=eu-west-2

Use aws codeartifact login --tool twine for publishing. --tool pip rewrites your pip index configuration for package installs, so if the CodeArtifact repository does not proxy public PyPI, local installs such as pip install -r requirements/dev.txt will fail until pip is pointed back at PyPI or the repository is configured with an upstream. Once the dev environment is already provisioned, python -m build --no-isolation avoids that isolated-env fetch.

Docker

Build and run the runtime host container:

docker compose --profile host up --build runtime-host

The runtime image is defined in docker/Dockerfile.

The top-level Docker path is intentionally single-node. The runtime host is designed to be horizontally scalable, and can be run in multiple instances behind a load balancer. The runtime does not currently have any built-in distributed execution capabilities, but it can be configured to use external services for distributed query execution and agent orchestration.

Identity And Auth

Langbridge runtime execution is workspace-scoped. The core identity carried through the runtime is:

• workspace_id
• actor_id
• roles
• request_id

The runtime host supports thin auth modes:

• none
• static_token
• jwt

Examples

• examples/golden/: golden production-style runtime demo surface
• examples/deployment/runtime_host/: self-hosted runtime host over a local config
• examples/deployment/runtime_host_sync/: connector sync example
• examples/deployment/customer_connector_image/: customer-specific Docker image with selected connector packages
• examples/connectors/shopify_sync/: live Shopify declarative connector sync example
• examples/connectors/hubspot_sync/: live HubSpot declarative connector sync example
• examples/sdk/semantic_query/: local SDK + semantic query walkthrough
• examples/sdk/federated_query/: local SDK + federated query walkthrough
• examples/legacy/complex_runtime/: legacy complex local runtime example retained while golden/ evolves

Supported Connectors

SQL

• Postgres
• MySQL
• Snowflake
• BigQuery
• Redshift
• Databricks
• SQLite More SQL connectors are in progress, and the connector framework is designed to make it easy to add new ones.

SaaS/API

• Shopify
• Stripe
• Salesforce
• HubSpot
• Zendesk
• Google Analytics More SaaS connectors are in progress, and the connector framework is designed to make it easy to add new ones.

NoSQL

• MongoDB More NoSQL connectors are in progress, and the connector framework is designed to make it easy to add new ones.

Vector

• Pinecone
• Faiss More vector connectors are in progress, and the connector framework is designed to make it easy to add new ones.

Future Work

Scale-out architecture with distributed coordinator and worker nodes

Note: the current product center is a strong single-node runtime host. Distributed coordinator/worker scale-out remains preview groundwork in this repo, not the primary v1 deployment path.

Documentation

Start with:

• docs/README.md
• docs/deployment/self-hosted.md
• docs/api.md
• docs/development/local-dev.md