About E2B_MCP
E2B_MCP is a custom MCP server and client for connecting to E2B, intended for users who want to run the connection without Claude app or Cursor. The README shows a Python server and a separate LlamaIndex client.
Key features
- 01Custom MCP server and client
- 02E2B connection
- 03Python startup commands
Use cases
- 01Connect to E2B through a custom MCP setup
- 02Run the provided server and LlamaIndex client
MCP support
It runs an MCP server for connecting to E2B and includes a client that connects to that server.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEE2B_MCP
English | 中文
Support connecting E2B via MCP with a custom server and client, without the need for tools like the Claude app or Cursor.
Environment configuration
conda create -n mcp python=3.12 -y
conda activate mcp
pip install -r requirements.txt
Run MCP
First, create a .env file and fill in the following variables:
E2B_API_KEY= ""
model=""
llm_api_key=""
llm_api_base = ""
E2B_API_KEY needs to be obtained from E2B , model is the name of the LLM, llm_api_base is the URL of the LLM, and llm_api_key is the API Key for the LLM.
Then start the server:
python ./e2b_mcp_server.py
Open a new terminal window and run the client:
python ./e2b_mcp_llamaindex_client.py
The result looks like this:
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.