Lisply MCP

What is Lisply MCP about?

Lisply MCP provides a Node.js middleware layer that connects Model Context Protocol (MCP) clients—such as Claude Desktop—to any Lisp‑based system that implements the lightweight Lisply protocol. By translating MCP tool calls into Lisp evaluation, HTTP requests, and debugger interactions, it lets large language models program, query, and debug Lisp environments directly.

How to use Lisply MCP?

1. Install prerequisites – Node.js 18+ and Docker 20+ on the same host.
2. Clone the repository

   git clone https://github.com/gornskew/lisply-mcp.git
   cd lisply-mcp
   

3. Run the wrapper (the entry point is scripts/mcp-wrapper.js). Example for a default Gendl backend:

   node scripts/mcp-wrapper.js --server-name gendl-ccl --http-port 9080
   

   The wrapper will automatically pull the appropriate Docker image, start the container, and expose the configured MCP tools.
4. Configure your AI agent – add an entry to the agent’s mcpServers section pointing to the wrapper script and the chosen HTTP port (see the README for full JSON examples).
5. Restart the AI agent – the new MCP server appears as <server-name>__lisp_eval, <server-name>__http_request, etc., ready for tool calls.

Key Features

• Lisp evaluation via lisp_eval tool (supports optional mode: "stdio" for raw REPL output).
• HTTP request forwarding with http_request tool for any backend‑exposed endpoint.
• Ping / health‑check tool to verify backend availability.
• Docker automation – automatic image selection, pulling, container start/stop, and volume mounting.
• Configurable communication – HTTP (default) or stdio modes, with optional SWANK/TELNET support.
• Multi‑server support – run several Lisply backends concurrently, each namespaced by a unique server name.
• Extensible environment variables and CLI flags for fine‑grained control (ports, mounts, timeouts, logging, etc.).

Use Cases

• Neuro‑Symbolic programming – let an LLM generate, compile, and test Lisp code on the fly.
• CAD automation – drive Gendl or similar Lisp‑based CAD kernels from an AI assistant.
• Education & exploration – interactively query Lisp REPLs, explore libraries, and debug via an LLM.
• Toolchain integration – embed Lisp‑driven logic into broader AI workflows (e.g., data preprocessing, symbolic reasoning).
• Multi‑environment orchestration – manage several Lisp runtimes (SBCL, CCL) side‑by‑side for comparative experiments.

FAQ

Q: Do I need to build the Docker image myself? A: No. The wrapper automatically pulls the public genworks/gendl image matching the current git branch and selected Lisp implementation. You can override the image with --docker-image if needed.

Q: Can I run the backend on a remote host? A: Yes. Set --backend-host (or LISPLY_BACKEND_HOST) to the remote address. The wrapper will skip Docker management and connect directly via HTTP.

Q: How do I disable the stdio mode for security? A: Use the --no-use-stdio flag or set the environment variable LISPLY_NO_USE_STDIO=true.

Q: What ports does the wrapper expose by default? A: Host HTTP 9081, HTTPS 9444, SWANK 4201, TELNET 4024. Internal container ports default to 9080, 9443, 4200, 4023 respectively.

Q: How are files shared between the host and the Lisp container? A: Use the --mount src:dst CLI option or the LISPLY_MOUNTS environment variable to bind‑mount directories (e.g., --mount /home/user/projects:/projects).

Q: Where are logs written? A: By default to /tmp/lisply-mcp-wrapper.log (configurable via --log-file).

Note: This branch is currently not stable for auto-starting containers. This will be corrected, but for now the more reliable way of starting a containerized Lisply-MCP environment is with the "Containerized Runnings" section of the skewed-emacs README. After the containers are started, then Claude Desktop will connect to them according to the example configurations below.

Model Context Protocol (MCP) Middleware for Lisp-based and Lisp-like Environments

This project is a Model Context Protocol (MCP) middleware that enables Large Language Models (LLMs) to interact with Lisp-based development and runtime environments using a lightweight protocol called Lisply.

Who Is this Meant For?

• AI practitioners curious about Lisp
• Lisp practitioners curious about AI
• Anyone interested in Neuro-Symbolic Programming
• Mechanical/Civil Engineers and Designers interested in CAD Automation and Knowledge Based Engineering
• Tinkerers, meddlers, and tamperers from all walks of life

What Is it Meant to Do?

The Lisply-MCP middleware connects MCP-capable AI Agent programs, or MCP Clients, such as ClaudeDesktop, to Lisp-based systems which support a REPL, or Read-Eval-Print Loop. The connection is meant to facilitate AI-assisted symbolic programming sometimes referred to as Neuro-Symbolic Programming. We have coined the term "Lisply" to refer to a lightweight protocol which most any Lisp-like system can implement to render it compatible with this Lisply-MCP middleware.

The idea is that the LLM will be able to generate and evaluate arbitrary Lisp expressions, including creating, compiling, loading, and testing entire files and projects.

Extra Quick Start

Follow the "Containerized Runnings" section of the skewed-emacs README.

This will get you a Docker Compose setup including a preconfigured containerized version of Lisply-MCP.

Quick Start

The following will get you up and running quickly with a minimal default configuration and a default public Common Lisp based backend running as a Docker container. See the main Contents below for more background and detailed configuration options.

1. Install

1. Install Node.js (18+ recommended). If on Windows, this can be installed directly in Windows or in WSL.

2. Install Docker (20+ recommended) on the same host as where the Node.js is installed.

3. Clone this lisply-mcp repository to a location where your MCP-capable AI Agent (e.g. Claude Desktop) can access it.

2. Configure your MCP-capabile AI Agent

Edit or create your AI Agent's configuration file as shown below. In the case of Claude Desktop, the configuration file is typically:

/mnt/c/Users/<user>/AppData/Roaming/Claude/claude_desktop_config.json

or

c:\Users\<user>\AppData\Roaming\Claude\claude_desktop_config.json

In the example below, replace /path/to/cloned/ with the correct path to the ./scripts/mcp-wrapper.js file from the cloned repo:

{
  "mcpServers": {
    "gendl-ccl": {
      "command": "node", 
      "args": [
        "/path/to/cloned/lisply-mcp/scripts/mcp-wrapper.js",
        "--server-name", "gendl-ccl",
	"--http-port", "9080"
      ]
    }
  },
  {
    "gendl-sbcl": {
      "command": "node", 
      "args": [
        "/path/to/cloned/lisply-mcp/scripts/mcp-wrapper.js",
        "--server-name", "gendl-sbcl",
	"--http-port", "9090"
      ]
    }
  },

  { 
    "skewed-emacs": {
      "command": "node", 
      "args": [
        "/path/to/cloned/lisply-mcp/scripts/mcp-wrapper.js",
        "--server-name", "skewed-emacs",
	"--http-port", "7080"
      ]
    }
  }

  
}

Or in a WSL scenario (where the Claude Desktop is running in the Windows host):

{
  "mcpServers": {
    "gendl-ccl": {
      "command": "wsl", 
      "args": [
        "node /path/to/cloned/lisply-mcp/scripts/mcp-wrapper.js",
        "--server-name", "gendl-ccl",
	"--http-port", "9080"
      ]
    }
  },
  {
    "gendl-sbcl": {
      "command": "wsl", 
      "args": [
        "node /path/to/cloned/lisply-mcp/scripts/mcp-wrapper.js",
        "--server-name", "gendl-sbcl",
	"--http-port", "9090"
      ]
    }
  },

  { 
    "skewed-emacs": {
      "command": "wsl", 
      "args": [
        "node /path/to/cloned/lisply-mcp/scripts/mcp-wrapper.js",
        "--server-name", "skewed-emacs",
	"--http-port", "7080"
      ]
    }
  }
  
}

See the main Contents below for further configuration options, for example how to have your ~/projects/ filesystem directory be shared ("mounted") from your host to the default Lisply backend, or how to specify an alternative Lisply backend container or service host/port.

Each server operates independently, allowing you to work with multiple Lisp environments simultaneously without tool name conflicts.

3. Restart your AI Agent and Test

With the above configuration in place, your freshly restarted AI Agent will now have access to an MCP server called lisply-gendl, with a gendl__lisp_eval MCP tool (among a few other tools discussed in the main Contents below). Note that tools are automatically prefixed with the server name to avoid conflicts when running multiple Lisply servers.

In order to test your setup, you can prompt your LLM as follows:

Evaluate (+ 1 2 3) using the gendl__lisp_eval tool, and let me know the result.

The LLM should invoke the requested evaluation and respond with 6 as expected. Feel free to experiment with more complex expressions before proceeding.

How Does the Default Minimal Configuration Work?

The minimal default configuration described in the Quick Start aboves will pull and run a Gendl docker container which contains a Common Lisp superset sporting a standard REPL (Read-Eval-Print Loop). Note a second Lisply backend implementation for Emacs lisp also exists, within the Skewed Emacs project.

System Overview

The Lisply MCP middleware is implemented as a Javascript program meant to run in Node.js, and provides a bridge between your AI Agent and any compliant Lisply backend system. This wrapper enables the AI Agent to:

1. Evaluate Lisp code in the Lisply Backend and receive the results.
2. Make HTTP requests to any web endpoints implemented in the backend.
3. Access introspection and documentation lookup facilities in the LB using Lisp evaluation.
4. Create, manipulate, compile, load, and analyze files, again using Lisp evaluation.
5. Interact with Lisp debuggers (for locally running backends).

Lisply is a lightweight protocol that specifies a minimal yet flexible set of HTTP and standard input/output interfaces, a standard set of environment variables, Docker container image naming conventions, and several optional capabilities to facilitate AI agents controlling your running Lisp system.

Architecture

The diagram below roughly captures how the components interact:

The middleware handles:

1. Starting and managing a Lisply-compliant Docker container if needed
2. Translating Lisp evaluation requests between the MCP protocol and the backend Lisply API
3. Error handling, Lisp debugger interaction, and logging

Security Considerations

Because Lisply-MCP allows arbitrary Lisp code to be evaluated against a running Lisp-based backend, there are certain risks in case the LLM were to go "haywire." Therefore, best practices are:

• Allow the wrapper to connect only to a containerized version of a Lisply backend. If overriding default host/port, the wrapper will happily connect to any live Lisply-compliant http port. Avoid allowing this to happen for any http ports being served by programs running directly on your host.

• Make sure not to mount any non-expendable directories to that container (see directory mounting configuration instructions below)

• Consider taking steps to limit RAM and CPU usage of the container.

Code Modules/Files

• lib/config.js: Configuration loading and environment handling
• lib/logger.js: Logging functionality
• lib/docker.js: Docker container management
• lib/server.js: HTTP server and MCP wrapper implementation
• lib/utils.js: Utility functions for response handling
• handlers/: Tool-specific request handlers
  • initialize.js: Initialization handler
  • toolsList.js: Tools list handler
  • toolCall.js: Main tool call dispatcher
  • httpRequest.js: HTTP request handler
  • ping.js: Ping handler
  • lispEval.js: Lisp evaluation handler
• mcp-wrapper.js: <--- Main entry point <---

Detailed Installation

1. Clone this repository:

git clone https://github.com/gornskew/lisply-mcp.git

2. Install the required dependencies (optional, as the wrapper auto-installs dependencies):

cd lisply-mcp/scripts
npm install # optional - the script will attempt to do this also if needed
chmod +x mcp-wrapper.js # needed on some systems

3. Ensure Docker is installed on your system.

4. Test the script:

node mcp-wrapper.js --help

Advanced Configuration

Optional settings for advanced users, with defaults suitable for most cases:

Command-Line Arguments

Options:
  -H, --backend-host <host>            Lisply server host (default: 127.0.0.1)
  --swank-host-port <port>             SWANK port on host system (external) (default: 4201)
  --http-host-port <port>              HTTP port on host system (external) (default: 9081)
  --https-host-port <port>             HTTPS port on host system (external) (default: 9444)
  --telnet-host-port <port>            TELNET port on host system (external) (default: 4024)
  --http-port <port>                   HTTP port inside container (internal) (default: 9080)
  --https-port <port>                  HTTPS port inside container (internal) (default: 9443)
  --swank-port <port>                  SWANK port inside container (internal) (default: 4200)
  --telnet-port <port>                 TELNET port inside container (internal) (default: 4023)
  --image-base-name <n>                Base name for Docker image (default: dcooper8/gendl)
  --image-branch <branch>              Branch to use for Docker image (default: auto-detected)
  --docker-image <image>               Full Docker image for backend (overrides base name and branch)
  --lisp-impl <impl>                   Lisp implementation to use, ccl or sbcl (default: ccl)
  --no-auto-start                      Do not auto-start backend Docker container if not running
  --docker-socket <path>               Path to Docker socket (default: /var/run/docker.sock)
  --log-file <path>                    Path to log file (default: /tmp/lisply-mcp-wrapper.log)
  --debug                              Enable debug logging
  --mount <mounts...>                  Mount volumes in format "src:dst" (can specify multiple times)
  --start-http                         Start HTTP service in backend container (default: true)
  --start-https                        Start HTTPS service in backend container (default: false)
  --start-swank                        Start SWANK service in backend container (default: true)
  --start-telnet                       Start TELNET service in backend container (default: false)
  --no-use-stdio                       Disable stdio capability for local containers (default: false)
  --repl-prompt <pattern>              REPL prompt pattern to detect Lisp evaluation completion (default: ?)
  --eval-timeout <ms>                  Timeout for Lisp evaluation in milliseconds (default: 30000)
  --endpoint-prefix <prefix>           Prefix for all endpoints (default: lisply)
  --lisp-eval-endpoint <n>             Endpoint name for Lisp evaluation (default: lisp-eval)
  --http-request-endpoint <n>          Endpoint name for HTTP requests (default: http-request)
  --ping-endpoint <n>                  Endpoint name for ping (default: ping-lisp)
  --server-name <name>                 MCP server name for tool prefixing (default: lisply-mcp)
  -h, --help                           Display help for command

Environment Variables

The script also supports configuration via environment variables. You can specify variables with the "LISPLY_" prefix or with no prefix:

Note: It is important to keep straight the difference between host ports (listening on and reachable from the host system) and container ports (internal to the container, visible to the Lisply backend service process):

Docker Integration

Lisply-MCP can interact with both local and remote Lisply backends. For the local case, the middleware can automatically run Docker commands to pull and manage the appropriate Lisply backend container.

Docker Image Selection

The middleware selects a default Docker image name based on the detected current git branch of your Lisply-MCP repository:

1. The Lisply Docker image naming convention follows the pattern: ${DOCKER_USER}/${IMAGE_BASE}:${IMAGE_BRANCH}-${LISP_IMPL}

   • ${DOCKER_USER} Username at hub.docker.com. defaults to genworks.
   • ${IMAGE_BASE} Main name of the Lisply backend. Defaults to gendl.
   • ${IMAGE_BRANCH} defaults to the current git branch name where the wrapper script is situated, with any slashes (/) converted to double hyphens (--)
     • For example, release/1598 becomes release--1598 in the image tag
     • devo branch will use the image tag devo
     • If no git branch is detected, defaults to master.
   • ${LISP_IMPL} is the Lisp implementation in case the base Lisply backend sports multiple available Lisp flavors (e.g., ccl, sbcl are available for current public Gendl builds).

2. The middleware will attempt to pull a newer image if one exists:

   • First tries to pull a newer image from Docker Hub.
   • If pull fails or local is up to date, uses the local one.

3. You can override the automatic selection with:

   • The --docker-image command-line argument (overrides --image-base-name and --image-branch entirely)
   • The --image-base-name and/or --image-branch arguments
   • The LISPLY_DOCKER_IMAGE environment variable
   • The LISPLY_IMAGE_BASE and LISPLY_IMAGE_BRANCH environment variables

4. For the Lisp implementation:

   • Specify with --lisp-impl (ccl or sbcl for current gendl builds)
   • Or use the LISPLY_LISP_IMPL environment variable
   • Defaults to ccl if not specified, sbcl is also a valid choice for the default Gendl images.

DockerHub Authentication

The wrapper will attempt to log in to DockerHub using stored credentials. However, the default container images are public and should be available anonymously without docker login.

Volume Mounting

You can mount host directories into the backend Lisply container to share files between your host system and the container (note multiple mount points can be specified):

{
  "mcpServers": {
    "lisply-gendl-4": {
      "command": "node",
      "args": [
        "/path/to/cloned/lisply-mcp/scripts/mcp-wrapper.js",
        "--mount", "/home/user/projects:/projects",
        "--mount", "/home/user/data:/data"
      ]
    }
  }
}

Or using environment variables:

LISPLY_MOUNTS=/home/user/projects:/projects,/home/user/data:/data node mcp-wrapper.js

Note the container runs with a certain UID, typically defaulting to 1000. This may cause unexpected file ownerships if the Lisply backend is writing to a mounted directory. This can be solved with docker exec by sending commands to the container to change the UID of the user running the service in the container. This behavior is expected to be automated in a future version of this project. A possible command could look like e.g.:

docker exec lisply-mcp-<hash> usermod -u 1001 lisply-user

Existing Service Detection

The wrapper will check if a Lisply service is already running on the specified http host and ports and use it if it exists, before attempting to pull and/or start a container.

Existing Services Override Local Container Settings

When an existing service is detected on the specified host and port, all Docker-related settings will be ignored:

• --docker-image, --image-base-name, --image-branch, and --lisp-impl
• --mount volume options
• --start-* service flags
• --*-port internal container port settings
• --docker-socket path
• --no-auto-start flag

In this case, the wrapper will log messages about which settings are being ignored.

Communication Modes

This middleware supports two primary modes of communication with configured Lisply backends: HTTP mode and stdio (Standard Input/Output) mode.

HTTP Mode

HTTP mode is the default communication method and works with both local and remote Lisply backends. This mode uses the standard HTTP endpoints that all Lisply backends are required to implement.

Characteristics:

• Structured responses with separate result, stdout, and error fields
• Suitable for most casual use cases
• Response format: {Result: <result>, Stdout: <output>, Error: <any error>}

Example response in HTTP mode:

{"Result": "6", "Stdout": "This is a message to standard output"}

Stdio Mode

Stdio mode provides more of a raw REPL experience for the LLM and enables the LLM to engage in interactive debugging. This mode expects to leverage the backend's native REPL interface and any included command-driven debugger.

Characteristics:

• Raw REPL-like output without structured formatting
• Support for interactive debugger when errors occur
• Only available for local containers started by this middleware
• Ideal for development, debugging, and complex interactions
• Captures standard output followed by return-value of evaluated expressions in same stream, so the LLM will have to distinguish these just as a human user would

Debugger Support: When an error occurs in stdio mode, the Lisp debugger can be interacted with. The wrapper detects debugger prompts and provides metadata about the debugger state to the AI Agent. This functionality relies on hardcoded prompt patterns in the wrapper code which would need to be augmented to support new Lisply backends with different REPL and debugger prompts (patches welcome).

Mode Selection:

• Default mode is HTTP.
• To use stdio mode for a particular tool call, ask the LLM to specify mode: "stdio" in the lisp_eval tool parameters.
• Stdio mode can be banned for the session by configuring with the --no-use-stdio flag or LISPLY_NO_USE_STDIO=true.

If stdio mode is requested but banned or otherwise not available, the wrapper will fall back to HTTP mode. LLM callers using stdio mode need to be aware of this, because the response from the HTTP fallback comes packaged in JSON instead of in raw format.

Usage Examples

All the examples below can be tested on command line and used in claude_desktop_config.json configuration (see Claude Desktop Configuration).

Running in a Container

If running the wrapper itself inside a container, make sure to mount the Docker socket (and some other port tricks may be necessary):

docker run -v /var/run/docker.sock:/var/run/docker.sock -v /path/to/scripts:/app node:18 node /app/mcp-wrapper.js

Adding a Separate, Compatible Filesystem MCP Server

Below is a claude_desktop_config.json which sets up a filesystem mcp server as well as our lisply-mcp-1 server, with a common mount shared between the two mcp servers:

{
  "mcpServers": {
    "filesystem": {
      "command": "wsl",
      "args": [
        "docker",
        "run",
        "-i",
        "--rm",
        "-u",
        "1000:1000",
        "--mount",
        "type=bind,src=/home/user/projects,dst=/projects",
        "mcp/filesystem",
        "/projects"
      ]
    },
    "lisply-gendl": {
      "command": "wsl",
      "args": [
        "node",
        "/home/user/projects/lisply-mcp/scripts/mcp-wrapper.js",
        "--server-name", "gendl",
        "--mount", "/home/user/projects:/projects"
      ]
    }
  },
  "globalShortcut": ""
}

Tool Details for Claude

Lisp Evaluation Tool (<server>__lisp_eval)

The lisp_eval tool (prefixed with the server name, e.g., gendl__lisp_eval) allows Claude to evaluate Lisp code directly within the Lisply environment with these parameters:

• code (required): The Lisp code to evaluate
• package (optional): The package to use for the evaluation
• mode (optional): The mode to use to talk to Lisply
  • http (default): Uses HTTP communication for structured responses
  • stdio: Uses standard input/output communication for a raw REPL experience

Mode Comparison:

HTTP Request Tool (<server>__http_request)

The http_request tool (prefixed with the server name, e.g., gendl__http_request) enables the AI Agent to interact with any HTTP endpoint exposed by the Lisply backend (the following example works with our default backend, which has a built-in /color-map http endpoint):

{
  "path": "/color-map",
  "method": "GET",
  "headers": {
    "Accept": "application/json"
  }
}

Ping Tool (<server>__ping_lisp)

The ping_lisp tool (prefixed with the server name, e.g., gendl__ping_lisp) lets Claude confirm that the Lisply server is running:

<server>__ping_lisp()

Real-World Examples

Example 1: Creating a Parametric Box

In this example, Claude creates a parametric box in the Lisply environment and then modifies its properties based on user requirements.

User: "Can you create a box with width 10, height 5, and depth 3? Then show me how to change the height to 8."

Claude:

I'll create a parametric box using the lisp_eval tool, then show you how to modify its height.

First, let's create the box with the specified dimensions:

(in-package :gdl-user)

;; First, create a box with the specified dimensions
(defparameter *my-box* (make-object 'box 
                         :width 10 
                         :height 5 
                         :length 3))

;; Let's verify the dimensions
(list (theo *my-box* width)
      (theo *my-box* height)
      (theo *my-box* length))

Now, let's change the height from 5 to 8:

;; Change the height using setf with accessor
(theo *my-box* (set-slot! :height 8))

;; Alternatively, we could create a new box
(defparameter *new-box* (make-object 'box 
                         :width 10 
                         :height 8  ;; Updated height
                         :length 3))

;; Verify the new dimensions of original box
(list (theo *my-box* width)
      (theo *my-box* height)
      (theo *my-box* length))

This box can be visualized by creating a web interface or using a built-in gendl visualization tool such as geysr. See Gendl Documentation for details.

Example 2: Demonstrating the Difference Between HTTP and Stdio Modes

User: "Can you show me the difference between HTTP and stdio modes by evaluating a simple expression that prints something to standard output and returns a value?"

AI Agent:

I'll demonstrate the difference between HTTP and stdio modes by evaluating a simple Lisp expression that both prints output and returns a value.

First, let's use HTTP mode (the default):

(progn 
  (format t "This is a message to standard output~%") 
  (+ 1 2 3))

Response in HTTP mode:

{"Result": "6", "Stdout": "This is a message to standard output"}

Now, let's use stdio mode for the same expression:

;; Using mode: stdio
(progn 
  (format t "This is a message to standard output~%") 
  (+ 1 2 3))

Response in stdio mode:

This is a message to standard output
6

Notice the difference: HTTP mode provides a structured response with labeled Result and Stdout sections, while stdio mode gives you the raw REPL output exactly as it appears in the Lisp REPL.

Stdio mode is particularly useful for debugging because it can show you interactive debugger prompts. For example, if we introduce an error:

;; Using mode: stdio
(progn
  (format t "About to generate an error~%")
  (/ 1 0))

In stdio mode, you might see something like:

About to generate an error
> Error: Division by zero
> While executing: /
> Type :help for debugging options

This allows the LLM to interact with the debugger directly. In HTTP mode, you would just get an error message without the interactive capabilities.

Troubleshooting

Common Issues and Solutions

Container Won't Start

If the Lisply container fails to start:

1. Check if Docker is running:

docker info

2. Check if the ports are already in use:

sudo lsof -i :4201
sudo lsof -i :9081

3. Verify that the Docker image exists:

docker images | grep genworks

4. Try pulling the image manually:

docker pull genworks/gendl:master-ccl

Connection Errors

If the LLM Agent / MCP Client cannot connect to the configured Lisply backend:

1. Check if the Lisply server is running:

docker ps | grep lisply

2. Check the wrapper's log file:

tail -f /tmp/lisply-mcp-wrapper.log

3. Check the Claude Desktop log file with Windows tools e.g. Notepad. This is typically in a location such as:

WSL/Linux:

/mnt/c/Users/<user>/AppData/Roaming/Claude/logs/mcp-server-lisply.log

Windows:

c:\Users\<user>\AppData\Roaming\Claude\logs\mcp-server-lisply.log

5. Try curling to the Lisply HTTP server:

curl http://localhost:9081/lisply/ping-lisp

6. Try connecting to the Lisply SWANK server (on default port 4201):

M-x slime-connect  ;; from emacs

Note that the setting up the Skewed-Emacs configuration will enable M-x slime-connect in your emacs.

Permission Issues

If you encounter permission errors:

1. Check Docker socket permissions:

ls -l /var/run/docker.sock

2. Make sure your user has permission to access Docker:

sudo usermod -aG docker $USER

3. Check mounted directory permissions:

ls -l /path/to/mounted/directory

Diagnostic Commands

Use these commands to diagnose general issues:

1. Check the middleware logs:

tail -f /tmp/lisply-mcp-wrapper.log

2. Check Docker container logs:

docker logs $(docker ps --filter "name=lisply-mcp" --format "{{.ID}}")

3. Check Lisply service status:

curl http://localhost:9081/lisply/ping-lisp

4. Verify Docker environment:

docker system info

License

This software is licensed under the GNU Affero General Public License v3.0 (AGPL-3.0), the same license used by Gendl.

License Implications

Simply using this MCP server to interact with a Lisply backend and obtain outputs does not trigger the requirements of the AGPL, e.g. you can use this wrapper to interact with Gendl without being required to share your code.

However, if you modify or extend this wrapper, or a license-compatible Lisply backend such as Gendl, and wish to distribute and/or host a service based on that result (commercial or not), then the AGPL would require you to share your modifications with the downstream recipients or users.

For applications that need to keep their source code closed, Genworks has begun offering an "escape clause" from AGPL restrictions for a 5% self-reported quarterly revenue royalty. More information and a payment gateway are available at royalties.genworks.com.

The full text of the license can be found in the COPYING.txt file in this directory.

MCP Server Registries

• MCPHub