mcpField
C

contextual

Local
@Contextual-LaboratoriesMemory & Knowledge

About contextual

Persistent memory for AI coding agents: local-first semantic search, dependency graphs, git history

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
  "mcpServers": {
    "contextual-laboratories-contextual": {
      "command": "uvx",
      "args": [
        "contextual-engine"
      ],
      "env": {
        "CONTEXTUAL_LOG_LEVEL": "<CONTEXTUAL_LOG_LEVEL>"
      }
    }
  }
}
Run commanduvx contextual-engine
Environment variables to set
CONTEXTUAL_LOG_LEVELPython logging level as an integer (e.g. 10=DEBUG, 20=INFO). Defaults to INFO.

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
pypicontextual-engine1.0.2

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

The maintainer has not added details yet. Check the README in the repository.

Comments

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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.