# langchain-mcp-client

> langchain-mcp-client — datalayer-langchain-mcp-client. Use this tool when you need to interact with LangChain models and manage context protocols for AI applications, solving problems related to model integration and data consistency. It provides an interface for inputting model requests and outputting relevant context-based responses. Ideal for use cases involving git version control and model development workflows.

Canonical page: https://skillsregistry.net/skills/datalayer-langchain-mcp-client  
JSON: https://api.skillsregistry.net/v1/skills/datalayer-langchain-mcp-client

## Description

🦜🔗 LangChain Model Context Protocol (MCP) Client

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-26

## Source

- **Source listing:** [GitHub](https://github.com/datalayer/langchain-mcp-client)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "datalayer-langchain-mcp-client"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/datalayer-langchain-mcp-client` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/datalayer-langchain-mcp-client/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt
