Add LangChain agent example connecting to ToolHive vMCP
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Description
User Story
As a ToolHive user attempting to build my own agent service with LangChain, I have no
reference implementation showing how to securely connect a LangChain agent to MCP
servers managed by ToolHive. Without this, I have to figure out the integration from
scratch.
Description
Create a self-contained LangChain agent example in the toolhive repository that
demonstrates connecting to a ToolHive-managed vMCP endpoint with Okta OIDC auth. This
should show users a realistic, runnable path for building LangChain agents on top of
ToolHive's MCP infrastructure.
Requirements
- Create
examples/agents/langchain/directory with a runnable Python example - Demonstrate how to initiate the SSO flow from the agent service to authenticate to a vMCP
- Show the agent invoking at least one MCP tool through the vMCP
- Include a
README.mdwith prerequisites, setup steps, and how to run - Keep dependencies minimal and pinned
Acceptance Criteria
- Example is checked into
examples/agents/langchain/in the toolhive repo - A user can follow the README and run the example against their own vMCP
- The example demonstrates successful tool invocation through the vMCP
- The SSO flow is initiated from within the agent service
- README explains what each part of the code is doing
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by locating the ToolHive vMCP endpoint and Okta OIDC authentication entry points, then create the runnable Python example under examples/agents/langchain/. Add examples/agents/langchain/README.md with prerequisites, pinned dependencies, setup, and explanation; done means a user can run the example, complete SSO, and invoke an MCP tool through their vMCP.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- ai, api, security
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 48/100