Which integrations are available for this server?

Allows web search via DuckDuckGo (no API key required), returning titles, URLs, and snippets.

How do I use lmstudio-agent-mcp?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@lmstudio-agent-mcp search for Python web scraping tutorials" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

lmstudio-agent-mcp

by oemoem12

Overview Schema Related Servers Score Discussions

Python

Hybrid

Agent MCP Server for LM Studio

WARNING

Do not install 1.2.0 — it has an undeclared mcp>=1.0.0 dependency that resolves to mcp 2.0.0, which renamed FastMCP to MCPServer and broke every console script with ModuleNotFoundError: No module named 'mcp.server.fastmcp'. Use 1.2.1 or later (the mcp pin is now >=1.0.0,<2.0.0). 1.2.1 has been verified end-to-end in a fresh venv: install works, all three console scripts start, and every tool responds correctly over stdio MCP.

A lightweight MCP (Model Context Protocol) server that provides local agent capabilities for LM Studio: file I/O, terminal execution, multi-engine web search, persistent key/value memory, and a pluggable skill system.

📦 PyPI 1.2.1 — pip install lmstudio-agent-mcp
🔌 Auto-registers with LM Studio — no manual config editing required
🛠 11 tools, ~14 kB wheel, no heavy dependencies

Features

Tool	Description
`agent_read_file`	Read text files with offset/limit pagination and encoding support
`agent_write_file`	Write or append to files, with optional parent directory creation
`agent_execute_command`	Execute shell commands with pipes, redirections, custom working directory, environment variables, and configurable timeout
`agent_web_search`	Search the web via DuckDuckGo, Bing, Google, or Baidu (switchable), returning titles, URLs, and snippets
`agent_memory_save`	Persist a key/value memory entry with category and tags
`agent_memory_load`	Load a single memory entry by key
`agent_memory_list`	List memory entries, optionally filtered by category/tag
`agent_memory_delete`	Delete a single memory entry
`agent_memory_search`	Full-text search across key, value, and tags (substring or regex)
`agent_list_skills`	Discover skills available in the configured skills directory
`agent_run_skill`	Invoke a discovered skill (Python, shell, or markdown)

Related MCP server: MCP Server Toolkit

Requirements

Python 3.10+
Dependencies listed in requirements.txt

Installation

pip install lmstudio-agent-mcp

After installation, three console scripts are available:

Script	Purpose
`lmstudio-agent-mcp`	Start the MCP server (`serve` is the default subcommand)
`lmstudio-mcp-setup`	Register this server with LM Studio's `mcp.json`
`lmstudio-mcp-config`	Print or write the LM Studio MCP config snippet

Auto-registration with LM Studio

The package registers itself with LM Studio automatically — no copy/paste required.

Editable / source install — a setuptools cmdclass hook appends an agent_mcp entry to ~/.lmstudio/mcp.json immediately after install.
Wheel install (e.g. from PyPI) — the first time lmstudio-agent-mcp starts it writes the entry silently. To trigger the registration right after install run:
```
lmstudio-mcp-setup
```

The function is idempotent: re-running it is a no-op. Pass --force to overwrite an existing entry. To opt out, set the environment variable LMSTUDIO_AGENT_NO_AUTOREGISTER=1 before starting the server.

A marker file ~/.lmstudio/.lmstudio_agent_mcp_installed is written next to mcp.json so the registration is not repeated unnecessarily. The generated snippet uses the installed lmstudio-agent-mcp console script as the command so no Python interpreter path is baked in:

{
  "mcpServers": {
    "agent_mcp": {
      "command": "/home/<you>/.local/bin/lmstudio-agent-mcp"
    }
  }
}

To print or write the config snippet manually:

lmstudio-mcp-config
# with overrides:
lmstudio-mcp-config --python /path/to/python --skills-dir ~/my_skills --memory-file ~/my_memory.json
# write directly (merges into existing mcp.json if present):
lmstudio-mcp-config --write ~/.lmstudio/mcp.json
# use the python module form instead of the console script:
lmstudio-mcp-config --no-console-script

Other install methods

# editable install (development)
git clone https://github.com/oemoem12/lmstudio-agent-mcp.git
cd lmstudio-agent-mcp
pip install -e .

# npm wrapper (thin shell around the Python package)
npm install -g lmstudio-agent-mcp

Usage with LM Studio

Restart LM Studio after running lmstudio-mcp-setup. The server will appear in the MCP list as agent_mcp. The CLI also generates a JSON snippet for mcp.json automatically; if you prefer to add it by hand:

{
  "mcpServers": {
    "agent_mcp": {
      "command": "/usr/bin/python3",
      "args": ["-m", "lmstudio_agent_mcp"]
    }
  }
}

The CLI automatically detects the current Python interpreter. Use --python to override it (e.g. for a virtualenv) and --skills-dir / --memory-file to customize where the server looks for skills and where it stores memory.

Usage with Other MCP Clients

The server uses stdio transport by default. Start it directly:

python3 -m lmstudio_agent_mcp

For remote access, switch to streamable HTTP:

import lmstudio_agent_mcp
lmstudio_agent_mcp.mcp.run(transport="streamable_http", port=8000)

Configuration

The server reads the following environment variables on startup:

Variable	Default	Purpose
`LMSTUDIO_AGENT_MEMORY_FILE`	`~/.lmstudio_agent_mcp/memory.json`	Path to the persistent memory store
`LMSTUDIO_AGENT_SKILLS_DIR`	`~/.agents/skills/`	Directory scanned for user-defined skills
`LMSTUDIO_AGENT_NO_AUTOREGISTER`	`0`	Set to `1` to disable silent autoregistration on first serve

The skills directory also accepts SKILL.md (with optional scripts/, reference/, etc. siblings) in addition to main.py / run.py directories.

Tool Reference

agent_read_file

Read the contents of a text file.

Parameter	Type	Default	Description
`path`	string	(required)	Absolute or relative path to the file
`offset`	int	`0`	Number of lines to skip from the beginning
`limit`	int \| null	`200`	Maximum number of lines to return (`null` = unlimited)
`encoding`	string	`"utf-8"`	Text encoding

agent_write_file

Write text content to a file.

Parameter	Type	Default	Description
`path`	string	(required)	Absolute or relative path to the file
`content`	string	(required)	Text content to write
`encoding`	string	`"utf-8"`	Text encoding
`append`	bool	`false`	If `true`, append instead of overwrite
`create_dirs`	bool	`true`	If `true`, create parent directories when missing

agent_execute_command

Execute a terminal command.

Parameter	Type	Default	Description
`command`	string	(required)	Shell command to execute
`working_directory`	string \| null	`null`	Working directory (defaults to server cwd)
`timeout`	float	`60.0`	Maximum execution time in seconds (1-600)
`env`	object \| null	`null`	Additional environment variables to set
`shell`	bool	`true`	Execute through system shell (required for pipes/redirects)

agent_web_search

Search the web using multiple search engines.

Parameter	Type	Default	Description
`query`	string	(required)	Search query (1-500 chars)
`engine`	string	`"duckduckgo"`	Search engine: `duckduckgo`, `bing`, `google`, or `baidu`
`num_results`	int	`5`	Maximum results to return (1-20)
`region`	string \| null	`null`	Region/locale code (e.g. `wt-wt`, `us-en`, `zh-cn`)

agent_memory_save

Persist a key/value memory entry to disk for cross-session recall.

Parameter	Type	Default	Description
`key`	string	(required)	Unique identifier (1-200 chars)
`value`	string	(required)	Content to remember
`category`	string	`"general"`	Logical bucket for filtering
`tags`	string[]	`[]`	Tags for retrieval filtering
`overwrite`	bool	`true`	If `false`, fail when key already exists

agent_memory_load

Load a single memory entry by key.

Parameter	Type	Default	Description
`key`	string	(required)	Key of the entry to load

agent_memory_list

List memory entries, optionally filtered by category and/or tag.

Parameter	Type	Default	Description
`category`	string \| null	`null`	Restrict to one category
`tag`	string \| null	`null`	Restrict to entries carrying this tag
`limit`	int	`100`	Maximum entries to return (1-1000)

agent_memory_delete

Delete a single memory entry.

Parameter	Type	Default	Description
`key`	string	(required)	Key of the entry to delete

agent_memory_search

Full-text search across key, value, and tags.

Parameter	Type	Default	Description
`query`	string	(required)	Substring or regex to search for (1-500 chars)
`use_regex`	bool	`false`	Treat the query as a regular expression
`category`	string \| null	`null`	Restrict the search to one category
`limit`	int	`20`	Maximum matches to return (1-200)

agent_list_skills

Discover skills available in the configured skills directory.

Parameter	Type	Default	Description
`skills_dir`	string \| null	`null`	Override the skills directory
`pattern`	string \| null	`null`	Glob pattern to filter skill names (e.g. `trans*`)

agent_run_skill

Invoke a discovered skill by name.

Parameter	Type	Default	Description
`name`	string	(required)	Skill name (subdirectory or filename without extension)
`input`	string	`""`	Primary input passed as the first argument
`args`	object	`{}`	Additional keyword arguments forwarded to the skill
`skills_dir`	string \| null	`null`	Override the skills directory
`timeout`	float	`60.0`	Maximum execution time in seconds (1-600)

Writing Skills

Place skills under the directory pointed to by LMSTUDIO_AGENT_SKILLS_DIR (default ~/.agents/skills/). Three skill types are supported:

Python skill (subdirectory)

skills/
└── summarize/
    ├── SKILL.md        # optional description (first paragraph is used)
    └── main.py         # must define `def run(input, **kwargs)`

# skills/summarize/main.py
def run(input: str, **kwargs) -> str:
    max_words = int(kwargs.get("max_words", 50))
    words = input.split()
    return " ".join(words[:max_words])

Python skill (single file)

# skills/translate.py
def run(input: str, **kwargs) -> str:
    target = kwargs.get("target", "zh")
    return f"[{target}] {input}"

Shell skill

# skills/count_lines.sh  (must be executable)
#!/usr/bin/env bash
echo "Lines: $(wc -l < "$1")"

The input parameter becomes $1; args become additional positional arguments.

Markdown skill

<!-- skills/cheatsheet.md -->
# Cheatsheet

Useful commands ...

A markdown skill simply returns the file contents when invoked.

Example: Memory + Skill Workflow

# 1) Save user preferences
agent_memory_save(key="user.lang", value="zh-CN", category="user", tags=["lang"])

# 2) Later, recall them
agent_memory_load(key="user.lang")

# 3) Run a custom skill
agent_run_skill(name="summarize", input="long text ...", args={"max_words": 20})

Security Notes

File paths are resolved to absolute paths; ~ expansion is supported
Large files (>10 MiB) are rejected to prevent memory exhaustion
Command execution has a configurable timeout (max 600s)
The memory file is rewritten atomically (temp file + rename) to prevent corruption
Do not expose this server to untrusted clients — agent_execute_command and agent_run_skill (Python/shell) can run arbitrary code

License

MIT

Install Server

license - permissive license

quality

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

–Release cycle

–Releases (12mo)

Commit activity

Resources

GitHub Repository

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