io.github.CloudCorpRecords/localmodels
Talk to a local Ollama server: list, pull, inspect, generate, chat and embed.
Install
Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).
@reneturcios/localmodelsclaude mcp add localmodels -- npx -y @reneturcios/localmodels@0.1.0 mcp
{
"mcpServers": {
"localmodels": {
"command": "npx",
"args": [
"-y",
"@reneturcios/localmodels@0.1.0",
"mcp"
]
}
}
}
ghcr.io/cloudcorprecords/localmodels:0.1.0claude mcp add localmodels -- docker run -i --rm ghcr.io/cloudcorprecords/localmodels:0.1.0 mcp
{
"mcpServers": {
"localmodels": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/cloudcorprecords/localmodels:0.1.0",
"mcp"
]
}
}
}
Documentation
From the project's README on GitHub, refreshed weekly. Links open on GitHub.
localmodels
localmodels puts a locally running Ollama server behind an MCP interface (with a matching CLI). List what is installed, pull or remove models, inspect one, then generate, chat, or embed — all against models that run on your own machine.
There is no API key and no account. The server address comes from
OLLAMA_HOST and defaults to http://127.0.0.1:11434. A value
without a scheme gets http:// in front of it, and trailing slashes
are ignored. If no Ollama server is reachable, calls fail with the
underlying connection error — they never invent an empty result.
Install
npx @reneturcios/localmodels list
docker run -i ghcr.io/cloudcorprecords/localmodels
In a container, point OLLAMA_HOST at the host (for example with
host networking), since 127.0.0.1 inside the container is the
container itself.
CLI
localmodels list
localmodels show llama3.2
localmodels pull qwen2.5
localmodels delete old:model
localmodels copy llama3.2 my-llama
localmodels generate llama3.2 "Write a haiku about autumn"
localmodels chat llama3.2 "Hello!"
localmodels embed nomic-embed-text "some text to embed"
localmodels running
localmodels version
localmodels --version
Exit codes: 0 success, 1 server/lookup error, 2 usage error.
MCP server
npx -y @reneturcios/localmodels mcp
{
"mcpServers": {
"localmodels": {
"command": "npx",
"args": ["-y", "@reneturcios/localmodels", "mcp"],
"env": { "OLLAMA_HOST": "http://127.0.0.1:11434" }
}
}
}
The env block is optional; the default address is used without it.
Tools
| Tool | Input | Upstream route |
|---|---|---|
list_models | — | GET /api/tags |
show_model | model | POST /api/show |
pull_model | model | POST /api/pull (stream: false) |
delete_model | model | DELETE /api/delete |
copy_model | source, destination | POST /api/copy |
generate_completion | model, prompt, system (optional) | POST /api/generate (stream: false) |
chat_completion | model, messages (array of {role, content}) | POST /api/chat (stream: false) |
create_embedding | model, input | POST /api/embed |
list_running_models | — | GET /api/ps |
get_version | — | GET /api/version |
Development
npm install
npm run build
npm test
npm run dev
Tests run entirely on fake-fetch fixtures; no live Ollama server is required or contacted.
License
MIT — see LICENSE.
Frequently asked questions
What is io.github.CloudCorpRecords/localmodels?
Talk to a local Ollama server: list, pull, inspect, generate, chat and embed.
How do I install io.github.CloudCorpRecords/localmodels?
It runs on your machine. In Claude Code: claude mcp add localmodels -- npx -y @reneturcios/localmodels@0.1.0 mcp. For other clients, paste the JSON configuration from this page into their MCP settings.
Does io.github.CloudCorpRecords/localmodels need an API key?
Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.
Is io.github.CloudCorpRecords/localmodels open source?
Yes. Its code is on GitHub under the MIT license.
Who maintains io.github.CloudCorpRecords/localmodels?
It is published by CloudCorpRecords. AI.tn lists it but does not maintain or endorse it.
From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.