Machai

machanism-org4stars

Automate application assembly using semantic search for smart library selection on the Machanism platform.

1# Machai

README.mdMCP server

Transport: stdio
Status: Local

Power your agent

Add this server

Install from the publisher. Not a PlugMCP endpoint.

Run on PlugMCP

Host a copy with our keys and logs.

No packaged release in the registry yet. Follow the repository README.

RepositoryPublisher installStep-by-step: add this in Claude

Remote URL or a command on your machine? How the two installs differ

Run on PlugMCP

Host a copy with our keys and logs.

A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.

Launch

Server facts

Local

Transport: stdio
License: Apache-2.0
Last checked: 2026-10-28

Stars: 4
Tools: —
Uptime: —

Tools

No tool list yet. Remote servers get one after the first health check.

FAQ

Questions

How do I install Machai?

Copy the stdio config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.

Does Machai need an API key?

No required environment variable is listed on this record.

What transport does Machai use?

Machai runs locally over stdio.

When was Machai last checked?

Last checked 2026-10-28. Automate application assembly using semantic search for smart library selection on the Machanism platform.

From the publisher

Documentation

Machai Project

Machai is a multi-module Java toolkit for GenAI-enabled developer automation. It provides provider-neutral generative-AI access, embedding support, Bindex library discovery, Model Context Protocol (MCP) servers, Maven integrations, and Ghostwriter workflows for repeatable, maintainable AI-assisted development.

Cloning and Getting Started

To clone and set up this project locally, follow these steps:

Clone the repository:

git clone https://github.com/machanism-org/machai.git
cd machai
git submodule update --init --recursive

Build the project using Maven:
```
mvn clean install
```

Modules

Name	Description
Project Layout	Utility library for describing, detecting, and resolving conventional project directories. It gives build tools, scanners, generators, and plugins a consistent model for source, test, resource, and documentation locations across Maven, Gradle, JavaScript, Python, and fallback layouts.
GenAI Client	Provider-neutral Java library for generative-AI integrations. It supports prompt execution, embeddings, provider resolution, usage tracking, web search, MCP servers, and registration of Java methods as AI-callable tools, prompts, and resources.
Machai MCP Server	Java 17 Model Context Protocol server runtime that exposes functional tools and prompts through STDIO or HTTP, including stateless and streamable HTTP modes; domain-specific tools remain in separate runtime libraries.
MCP Server Maven Plugin	Maven plugin that starts the Machai MCP Server for a Maven project over HTTP. Its aggregator goals provide stateless or streamable transport and supply project metadata, parameters, tools, and project-directory context.
Bindex Core	Core services for Bindex metadata retrieval, registration, semantic library recommendation, classification, embeddings, and MongoDB-backed persistence. It supports Ghostwriter, Maven plugins, MCP workflows, and AI-assisted project assembly.
Ghostwriter	AI-powered project-wide processing engine and command-line tool for source code, tests, documentation, site content, configuration, diagrams, and other project files. It uses embedded guidance and reusable Acts for repeatable AI-assisted automation.
Ghostwriter-Py (mgw)	Python 3.9-or-newer API and command-line wrapper around Ghostwriter. It bundles the Java runtime with `mgw`, validates `JAVA_HOME`, and starts JPype lazily. Its `gw`, `gdp`, and `adw` functions support CLI invocation, guidance processing, and Act execution; direct processor calls can resolve local JARs or Maven coordinates through `jgo` and return ordinary Python results.
GW Maven Plugin	Primary Maven adapter for Ghostwriter. It runs guidance-driven processing or named and prompt-based Acts over selected project files, with project-wide and per-module goals, Maven settings integration, and Java class-introspection tools.
Ghostwriter MCP Server	Runnable Java 17 MCP server that packages Ghostwriter workflows, Bindex metadata services, and the Machai MCP runtime. It exposes project-assistance, metadata retrieval, registration, and library-recommendation capabilities through STDIO or HTTP.
Bindex Maven Plugin	Maven plugin that generates and registers Bindex metadata for Maven projects and reactor builds. It provides reactor-wide and per-module goals that delegate generation and registration to Ghostwriter and Bindex Core workflows.
Bindex MCP Server	Standalone Java 17 distribution packaging Bindex Core with the Machai MCP runtime. It exposes complete or GraphQL-filtered metadata retrieval, validation and registration from JSON, files, or URLs, schema access, and natural-language library recommendations through STDIO or HTTP. Recommendations use classification, embeddings, and MongoDB-backed search with language, layer, score, and version filters.

Project Structure

Machai is a Maven parent project that coordinates eleven cooperating modules: foundation libraries, core AI services, language integration, Maven build integrations, and ready-to-run MCP server distributions. Project Layout supplies shared directory resolution, and GenAI Client supplies provider, embedding, and tool abstractions. The Machai MCP Server provides the reusable MCP runtime; Bindex Core and Ghostwriter build on the foundation libraries; Ghostwriter-Py embeds the Ghostwriter processor for Python callers; Maven plugins invoke their corresponding runtime services; and the server distributions publish Bindex and Ghostwriter capabilities to MCP clients. External AI providers serve the GenAI client, while Maven builds invoke the plugins. Each module is a Git submodule, and each link targets its corresponding remote GitHub repository at the recorded submodule commit rather than a relative path in the parent repository.

The architecture groups the modules into foundation libraries, core services, language integration, Maven build integration, and ready-to-run MCP server distributions. External AI providers supply the GenAI client, Maven invokes the build plugins, and MCP clients consume the packaged server capabilities. Bindex Maven Plugin uses GW Maven Plugin and Bindex Core, while the Ghostwriter packaging profile includes Bindex tools, also available transitively to the Python integration. No rendered project-structure image is available in the configured site resources, so the overview remains textual.

Introduction

Applications can use the GenAI client directly, expose tools through MCP, discover reusable libraries through Bindex, or automate repository-wide updates to source code, tests, documentation, configuration, diagrams, and other project files with the Ghostwriter command line and Maven plugin. The modules are designed to work independently where appropriate and together for end-to-end AI-assisted development workflows.

Requirements and Build

JDK 17 or newer is required to build the complete reactor. Several libraries target Java 8 bytecode, while the MCP server components and Bindex Core require Java 17.
Apache Maven 3.8.1 or newer.
Git and network access to download dependencies.
Provider credentials and service configuration when running GenAI, Bindex, or custom functional-tool workflows.

Run the full verification suite with:

mvn clean verify

To build and stage the project site, first set MACHAI_SITE to a writable staging directory used by the site's post-processing configuration:

mvn clean install site site:stage

Set MACHANISM_PACK_DIR before running mvn -Ppack install when a packaging profile needs to create a CLI or server distribution. Reactor-wide packaging also builds the Python wrapper and requires Python 3.9 or newer with the build package installed (python -m pip install build). Set JAVA_HOME before using the Python wrapper.

Usage

Add a library dependency

Add a published module to your Maven project, selecting the version you require:

<dependency>
  <groupId>org.machanism.machai</groupId>
  <artifactId>genai-client</artifactId>
  <version>1.4.2</version>
</dependency>

See the selected module's documentation for provider configuration, API details, and workflow examples.

Run an MCP server

Build the Machai MCP server with its packaging profile, add functional-tool libraries to the runtime classpath, and start it in STDIO mode:

mvn -pl machai-mcp-server -Ppack install
java -cp path/to/machai-mcp-server.jar:path/to/functional-tools.jar org.machanism.machai.mcp.server.McpServer

Start HTTP mode on port 45000:

java -cp path/to/machai-mcp-server.jar:path/to/functional-tools.jar org.machanism.machai.mcp.server.McpServer --port 45000

These commands require the assembled JAR containing runtime dependencies; substitute its actual output path and your tool library paths. On Windows, quote the classpath and separate entries with ; instead of :, for example java -cp "path/to/machai-mcp-server.jar;path/to/functional-tools.jar" org.machanism.machai.mcp.server.McpServer --port 45000. Connect an HTTP MCP client to http://localhost:45000/mcp; add --session for streamable HTTP sessions.

Run Ghostwriter from Maven

Process guidance-tagged files:

mvn org.machanism.machai:gw-maven-plugin:gw

Run an Act or direct prompt for a selected path:

mvn org.machanism.machai:gw-maven-plugin:act -Dgw.act="review Focus on public APIs" -Dgw.path=src/main/java

Configure the required AI provider, model, credentials, Bindex repository, and tool-specific settings before running AI-backed workflows.

Use the CLI, Python wrapper, and metadata tools

From an unpacked Ghostwriter delivery pack, inspect the CLI options or process a selected path:

java -jar gw.jar --help
java -jar gw.jar src --projectDir .

With Python 3.9 or newer and JAVA_HOME configured, install the wrapper and inspect its CLI:

python -m pip install mgw
python -m mgw --help

The wrapper exposes gw, gdp, and adw for Python applications. Use Bindex Maven Plugin's bindex and register goals to generate and publish metadata, or their -per-module variants for reactor module processing. MCP Server Maven Plugin's stateless and streamable goals launch an HTTP endpoint from Maven with -Dmcp.port=45000 -Dmcp.config=gw.properties. The Ghostwriter and Bindex MCP distributions package their respective tools for MCP clients; consult the linked module documentation for service configuration and packaging details.

Troubleshooting and Debugging

Modules that include the SLF4J SimpleLogger binding can be configured with simplelogger.properties on the runtime classpath, commonly in src/main/resources. This example enables a global level and package-specific levels, writes to standard output, and configures the log layout:

org.slf4j.simpleLogger.defaultLogLevel=info
org.slf4j.simpleLogger.log.org.machanism=debug
org.slf4j.simpleLogger.log.org.machanism.machai=trace
org.slf4j.simpleLogger.logFile=System.out
org.slf4j.simpleLogger.showThreadName=true
org.slf4j.simpleLogger.showLogName=true
org.slf4j.simpleLogger.showShortLogName=true
org.slf4j.simpleLogger.levelInBrackets=true
org.slf4j.simpleLogger.showDateTime=true
org.slf4j.simpleLogger.dateTimeFormat=yyyy-MM-dd HH:mm:ss.SSS

Set org.slf4j.simpleLogger.logFile=System.err for standard error, or set it to a writable file path such as logs/machai.log; its parent directory must exist. Package-specific settings override the default level. Valid levels are trace, debug, info, warn, error, and off.

Override the same properties at launch without changing classpath resources:

java -Dorg.slf4j.simpleLogger.defaultLogLevel=debug -Dorg.slf4j.simpleLogger.log.org.machanism.machai=trace -Dorg.slf4j.simpleLogger.logFile=System.err -Dorg.slf4j.simpleLogger.showDateTime=true -jar machai-mcp-server.jar

Place JVM properties before -jar. If a change does not take effect, confirm that slf4j-simple is present at runtime, simplelogger.properties is on the effective classpath, and another SLF4J provider has not been selected.

Contributing

Open an issue for a bug, documentation gap, feature proposal, or design question.
Create a focused branch from main and keep changes limited to the stated problem.
Follow the existing Java and Markdown style, preserve guidance comments, and update relevant documentation when behavior changes.
Add or update tests, run mvn clean verify, and submit a pull request with a clear summary, testing details, and configuration or compatibility impact.
Address review feedback and keep the branch synchronized with the target branch.

License

Machai is distributed under the Apache License, Version 2.0.

Contact and Support

Machai project site
GitHub repository
GitHub issue tracker
Machanism organization
Maintainer: Viktor Tovstyi, [email protected]

Machai

machanism-org4stars

Automate application assembly using semantic search for smart library selection on the Machanism platform.

Knowledge Memory Documentation

Install Run on PlugMCP

GitHub Website

Run on PlugMCP

1# Machai

README.mdMCP server

Transport: stdio
Status: Local

Power your agent

Add this server

Install from the publisher. Not a PlugMCP endpoint.

Run on PlugMCP

Host a copy with our keys and logs.

No packaged release in the registry yet. Follow the repository README.

RepositoryPublisher installStep-by-step: add this in Claude

Remote URL or a command on your machine? How the two installs differ

Run on PlugMCP

Host a copy with our keys and logs.

A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.

Launch

Server facts

Local

Transport: stdio
License: Apache-2.0
Last checked: 2026-10-28

Stars: 4
Tools: —
Uptime: —

Tools

No tool list yet. Remote servers get one after the first health check.

FAQ

Questions

How do I install Machai?

Copy the stdio config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.

Does Machai need an API key?

No required environment variable is listed on this record.

What transport does Machai use?

Machai runs locally over stdio.

When was Machai last checked?

Last checked 2026-10-28. Automate application assembly using semantic search for smart library selection on the Machanism platform.

From the publisher

Documentation

Machai Project

Cloning and Getting Started

To clone and set up this project locally, follow these steps:

Clone the repository:

git clone https://github.com/machanism-org/machai.git
cd machai
git submodule update --init --recursive

Build the project using Maven:
```
mvn clean install
```

Modules

Name	Description
Project Layout	Utility library for describing, detecting, and resolving conventional project directories. It gives build tools, scanners, generators, and plugins a consistent model for source, test, resource, and documentation locations across Maven, Gradle, JavaScript, Python, and fallback layouts.
GenAI Client	Provider-neutral Java library for generative-AI integrations. It supports prompt execution, embeddings, provider resolution, usage tracking, web search, MCP servers, and registration of Java methods as AI-callable tools, prompts, and resources.
Machai MCP Server	Java 17 Model Context Protocol server runtime that exposes functional tools and prompts through STDIO or HTTP, including stateless and streamable HTTP modes; domain-specific tools remain in separate runtime libraries.
MCP Server Maven Plugin	Maven plugin that starts the Machai MCP Server for a Maven project over HTTP. Its aggregator goals provide stateless or streamable transport and supply project metadata, parameters, tools, and project-directory context.
Bindex Core	Core services for Bindex metadata retrieval, registration, semantic library recommendation, classification, embeddings, and MongoDB-backed persistence. It supports Ghostwriter, Maven plugins, MCP workflows, and AI-assisted project assembly.
Ghostwriter	AI-powered project-wide processing engine and command-line tool for source code, tests, documentation, site content, configuration, diagrams, and other project files. It uses embedded guidance and reusable Acts for repeatable AI-assisted automation.
Ghostwriter-Py (mgw)	Python 3.9-or-newer API and command-line wrapper around Ghostwriter. It bundles the Java runtime with `mgw`, validates `JAVA_HOME`, and starts JPype lazily. Its `gw`, `gdp`, and `adw` functions support CLI invocation, guidance processing, and Act execution; direct processor calls can resolve local JARs or Maven coordinates through `jgo` and return ordinary Python results.
GW Maven Plugin	Primary Maven adapter for Ghostwriter. It runs guidance-driven processing or named and prompt-based Acts over selected project files, with project-wide and per-module goals, Maven settings integration, and Java class-introspection tools.
Ghostwriter MCP Server	Runnable Java 17 MCP server that packages Ghostwriter workflows, Bindex metadata services, and the Machai MCP runtime. It exposes project-assistance, metadata retrieval, registration, and library-recommendation capabilities through STDIO or HTTP.
Bindex Maven Plugin	Maven plugin that generates and registers Bindex metadata for Maven projects and reactor builds. It provides reactor-wide and per-module goals that delegate generation and registration to Ghostwriter and Bindex Core workflows.
Bindex MCP Server	Standalone Java 17 distribution packaging Bindex Core with the Machai MCP runtime. It exposes complete or GraphQL-filtered metadata retrieval, validation and registration from JSON, files, or URLs, schema access, and natural-language library recommendations through STDIO or HTTP. Recommendations use classification, embeddings, and MongoDB-backed search with language, layer, score, and version filters.

Project Structure

Introduction

Requirements and Build

JDK 17 or newer is required to build the complete reactor. Several libraries target Java 8 bytecode, while the MCP server components and Bindex Core require Java 17.
Apache Maven 3.8.1 or newer.
Git and network access to download dependencies.
Provider credentials and service configuration when running GenAI, Bindex, or custom functional-tool workflows.

Run the full verification suite with:

mvn clean verify

To build and stage the project site, first set MACHAI_SITE to a writable staging directory used by the site's post-processing configuration:

mvn clean install site site:stage

Usage

Add a library dependency

Add a published module to your Maven project, selecting the version you require:

<dependency>
  <groupId>org.machanism.machai</groupId>
  <artifactId>genai-client</artifactId>
  <version>1.4.2</version>
</dependency>

See the selected module's documentation for provider configuration, API details, and workflow examples.

Run an MCP server

Build the Machai MCP server with its packaging profile, add functional-tool libraries to the runtime classpath, and start it in STDIO mode:

mvn -pl machai-mcp-server -Ppack install
java -cp path/to/machai-mcp-server.jar:path/to/functional-tools.jar org.machanism.machai.mcp.server.McpServer

Start HTTP mode on port 45000:

java -cp path/to/machai-mcp-server.jar:path/to/functional-tools.jar org.machanism.machai.mcp.server.McpServer --port 45000

Run Ghostwriter from Maven

Process guidance-tagged files:

mvn org.machanism.machai:gw-maven-plugin:gw

Run an Act or direct prompt for a selected path:

mvn org.machanism.machai:gw-maven-plugin:act -Dgw.act="review Focus on public APIs" -Dgw.path=src/main/java

Configure the required AI provider, model, credentials, Bindex repository, and tool-specific settings before running AI-backed workflows.

Use the CLI, Python wrapper, and metadata tools

From an unpacked Ghostwriter delivery pack, inspect the CLI options or process a selected path:

java -jar gw.jar --help
java -jar gw.jar src --projectDir .

With Python 3.9 or newer and JAVA_HOME configured, install the wrapper and inspect its CLI:

python -m pip install mgw
python -m mgw --help

Troubleshooting and Debugging

org.slf4j.simpleLogger.defaultLogLevel=info
org.slf4j.simpleLogger.log.org.machanism=debug
org.slf4j.simpleLogger.log.org.machanism.machai=trace
org.slf4j.simpleLogger.logFile=System.out
org.slf4j.simpleLogger.showThreadName=true
org.slf4j.simpleLogger.showLogName=true
org.slf4j.simpleLogger.showShortLogName=true
org.slf4j.simpleLogger.levelInBrackets=true
org.slf4j.simpleLogger.showDateTime=true
org.slf4j.simpleLogger.dateTimeFormat=yyyy-MM-dd HH:mm:ss.SSS

Override the same properties at launch without changing classpath resources:

java -Dorg.slf4j.simpleLogger.defaultLogLevel=debug -Dorg.slf4j.simpleLogger.log.org.machanism.machai=trace -Dorg.slf4j.simpleLogger.logFile=System.err -Dorg.slf4j.simpleLogger.showDateTime=true -jar machai-mcp-server.jar

Contributing

Open an issue for a bug, documentation gap, feature proposal, or design question.
Create a focused branch from main and keep changes limited to the stated problem.
Follow the existing Java and Markdown style, preserve guidance comments, and update relevant documentation when behavior changes.
Add or update tests, run mvn clean verify, and submit a pull request with a clear summary, testing details, and configuration or compatibility impact.
Address review feedback and keep the branch synchronized with the target branch.

License

Machai is distributed under the Apache License, Version 2.0.

Contact and Support

Machai project site
GitHub repository
GitHub issue tracker
Machanism organization
Maintainer: Viktor Tovstyi, [email protected]