Showing posts with label eclipse. Show all posts
Showing posts with label eclipse. Show all posts

Monday, August 25, 2025

Building MCP Servers: Dynamic Tool Groups

Currently, adding tools to MCP servers is a static process.  i.e. a new tool is designed and implemented, MCP meta-data (descriptions) added via annotations, decorators, or code, the new code is added to the MCP server,  things are compiled and started, tested, debugged, etc.

As well, there is currently no mcp concept of tool 'groups'...i.e. multiple tools that are grouped together based upon function, common use case, organization, or discoverability.  Most current MCP servers have a flat namespace of tools.

I've created a repo with a small set of classes, based upon the mcp-java-sdk and the mcp-annotations projects, that supports the dynamic adding and removing of tool groups from mcp servers.

In environments with the OSGi service registry, this allows the easy, dynamic, and secure (type safe) adding and removing of OSGi services (and/or remote services) to MCP servers.

Wednesday, August 20, 2025

Building MCP Servers: Alternative Transports

Many developers are creating their own MCP Servers, to integrate their applications and APIs with AI models in a consistent way across multiple models.

The MCP SDKs currently provide two transports:  stdio (standard io), and http sse.  

I've created a new open source repo for alternative mcp transports.  

The intention is to provide alternative transports with other hardware, security, and trust properties.  

The first instance is based upon Unix Domain Sockets, which restricts the inter-process communication to processes running on the same operating system.







Saturday, August 02, 2025

Building MCP Servers: Preventing AI Monopolies

I recently read an insightful article about using open protocols (MCP in this case) to prevent user context/data lock-in at the AI application layer:

Open Protocols Can Prevent AI Monopolies

In the spirit of this article, I've decided to make an initial code contribution to the MCP java sdk project



Monday, June 02, 2025

Remote Tools for Model Context Protocol (MCP) Servers

The Model Context Protocol (MCP) is a new protocol for integrating AI/LLMs with existing software services.  MCP Server Tools allow LLMs get additional context-relevant data, write/change remote data, and to take actions.

Most current MCP servers declare their tools statically.  When the MCP server starts up it's available tools and any tool meta-data (such as text descriptions of the tool behavior provided in decorators or annotations) are made available to MCP clients that connect to an MCP server.  The MCP client (LLM) can then call an available tool at the appropriate time, providing tool-specific input data, and the tool can take actions, get additional data, and provide those data to the client.

OSGi Remote Services/Remote Service Admin provides a open, standardized, multi-protocol, modular,  extensible way to discover, dynamically export and import, and secure inter-process communication between services.  Combining Remote Services with MCP Tool meta-data allows the creation of dynamic remote tools.

Remote Tools for MCP Servers

This README.md shows an example 'Arithmetic' service, with 'add' and 'multiply' tools defined and described via Java annotations to an ArithmeticTools service. The python MCP Server communicates with the Java Server (startup and after) to dynamically add to/update from its set of tools that it exposes to MCP Clients.

Here is a simple diagram showing the communication between and MCP client, the Python MCP Server, and a Java Arithmetic Service Server.

MCP Client (LLM)  <- MCP -> Python MCP Server <- Arithmetic Service -> Java Server

The ArithmeticTools service is a simple example, but exposes a powerful and general capability,  Arbitrary remote tool services may be declared and provided with the appropriate tool description meta-data, and then made dynamically available to any MCP servers created in Python, Java, or other languages.  Both the MCP and RS/RSA are transport agnostic, allowing the service developer and service provider to use the remote-tool-appropriate-and-secure communication protocol.  




Tuesday, October 19, 2021

OSGi Services with gRPC - Let's be reactive

ECF has just introduced an upgrade to the grpc distribution provider.   Previously, this distribution provider used ReaxtiveX java version 2 only.  With this release, ReactiveX java version 3 is also supported.

As many know, gRPC allows services (both traditional call/response [aka unary] and streaming services) to be defined by a 'proto3' file.  For example, here is a simple service with four methods, one unary (check) and 3 streaming (server streaming, client streaming, and bi-directional streaming)
syntax = "proto3";

package grpc.health.v1;

option java_multiple_files = true;
option java_outer_classname = "HealthProto";
option java_package = "io.grpc.health.v1.rx3";

message HealthCheckRequest {
  string message = 1;
}

message HealthCheckResponse {
  enum ServingStatus {
    UNKNOWN = 0;
    SERVING = 1;
    NOT_SERVING = 2;
    SERVICE_UNKNOWN = 3;  // Used only by the Watch method.
  }
  ServingStatus status = 1;
}

service HealthCheck {
  // Unary method
  rpc Check(HealthCheckRequest) returns (HealthCheckResponse);
  // Server streaming method
  rpc WatchServer(HealthCheckRequest) returns (stream HealthCheckResponse);
  // Client streaming method
  rpc WatchClient(stream HealthCheckRequest) returns (HealthCheckResponse);
  // bidi streaming method
  rpc WatchBidi(stream HealthCheckRequest) returns (stream HealthCheckResponse);
}
The gRPC project provides a plugin so that when protoc is run, java code (or other language code) is generated that can then be used on the server and/or clients.

With some additional plugins, the classes generated by protoc can use the ReactiveX API for generating code.   So, for example, here is the java code generated by running protoc, grpc, reactive-grpc, and the osgi-generator plugins on the above HealthCheck service definition.  

Note in particular the HealthCheckService interface generated by the osgi-generator protoc plugin:
package io.grpc.health.v1.rx3;

import io.reactivex.rxjava3.core.Single;
import io.reactivex.rxjava3.core.Flowable;

@javax.annotation.Generated(
value = "by grpc-osgi-generator (REACTIVEX) - A protoc plugin for ECF's grpc remote services distribution provider at https://github.com/ECF/grpc-RemoteServiceSProvider ",
comments = "Source: health.proto.  ")
public interface HealthCheckService {
    /**
     * <pre>
     *  Unary method
     * </pre>
     */
    default Single<io.grpc.health.v1.rx3.HealthCheckResponse> check(Single<io.grpc.health.v1.rx3.HealthCheckRequest> requests)  {
        return null;
    }
    /**
     * <pre>
     *  Server streaming method
     * </pre>
     */
    default Flowable<io.grpc.health.v1.rx3.HealthCheckResponse> watchServer(Single<io.grpc.health.v1.rx3.HealthCheckRequest> requests)  {
        return null;
    }
    /**
     * <pre>
     *  Client streaming method
     * </pre>
     */
    default Single<io.grpc.health.v1.rx3.HealthCheckResponse> watchClient(Flowable<io.grpc.health.v1.rx3.HealthCheckRequest> requests)  {
        return null;
    }
    /**
     * <pre>
     *  bidi streaming method
     * </pre>
     */
    default Flowable<io.grpc.health.v1.rx3.HealthCheckResponse> watchBidi(Flowable<io.grpc.health.v1.rx3.HealthCheckRequest> requests)  {
        return null;
    }
}

Note that it uses the two ReactiveX 3 classes: io.reactivex.rxjava3.core.Single, and io.reactivex.rxjava3.core.Flowable. These two classes provide api for event-driven/reactive sending and receiving of unary (Single) and streaming (Flowable) arguments and return values.

The ReactiveX API...particularly Flowable...makes it very easy to implement both consumers and implementers of the streaming API, while maintaining ordered delivery and non-blocking communication.

For example, this is a simple implementation of the HealthCheckService. Note how the Single and flowable methods are able to express the implementation logic through methods such as Flowable.map.
Here is a simple implementation of a consumer of the HealthCheckService.

The use of the ReactiveX API simplifies both the implementation and the consumer use of both unary and streaming services. As an added bonus: the reactive-grpc library used in the ECF Distribution provider provides *flow-control* using backpressure.

In next article I'll describe how OSGi Remote Services can be easily used to export, publish, discover, and import remote services with full support for service versioning, security, and dynamics. I'll also describe one can use tools like maven or bndtools+eclipse to generate source code (as above) from a proto3 file and easily run a generated service as an OSGi Remote Service.

Tuesday, August 03, 2021

gRPC Remote Services Development with Bndtools - video tutorials

Here are four new videos that show how to define, implement and run/debug gRPC-based remote services using bndtools, eclipse, and ECF remote services.

Part 1 - API Generation - The generation of a OSGi remote service API using bndtools code generation and the protoc/gRPC compiler. The example service API has both unary and streaming gRPC method types supported by the reactivex API.

Part 2 - Implementation and Part 3 - Consumer - bndtools-project-template-based creation of remote service impl and consumer projects

Part 4 - Debugging - Eclipse/bndtools-based running/debugging of the remote service creating in parts 1-3.

Tuesday, June 22, 2021

gRPC and OSGi Remote Services

 gRPC is a popular framework for creating high-performance remote procedure call-based microservices.  

OSGi Remote Services is a transport-agnostic specification for creating dynamic, versionable, modular, remote services.

The ECF project provides an open implementation of the OSGi Remote Services spec, and has a provider implementation based-upon gRPC.   What this means is that gRPC can be used to create and run as an OSGi remote service, with all the support for service dynamics (particularly important for network-based services), versioning, and other features provided by OSGi remote services.

The architectural fit between gRPC and OSGi Remote Services is very good, since gRPC is concerned with transport-level efficiency (i.e. http/2, binary serialization format), and OSGi Remote Services are completely transport-agnostic, and focuses instead upon service-level concerns (e.g. dynamics, versioning, and service discovery).

gRPC offers support for server and client-based streaming.   In ECF's implementation, streaming rpcs are mapped to the reactivex api.  This means that consumers and implementers of a streaming rpc can simply call methods and provide callbacks (using Flowable), and non-blocking streaming calls will be made.  In addition, the use of reactivex and backpressure will result in transport-level flow control for these streaming APIs!

Another advantage of gRPC for OSGi remote services is it's polyglot nature.   This means that if (for example) a gRPC remote service is run as an OSGi/Java server, clients can be easily implemented in any of the languages supported by gRPC.  As well, servers written in some other language can easily created and accessed from OSGi consumers.  An example of this is the ECF etcd3 discovery provider, which communicates with an etcd server (written in Go) to publish and discover OSGi remote services.

Finally, with bndtools (an Eclipse plugin for OSGi bundle development), ECF Remote Service workspace template, and it's support for generating code as part of Eclipse's incremental build, gRPC code generation can be seemlessly integrated into the Eclipse development environment so that gRPC code generation, compile, and bundle packaging can happen immediately and continuously as part of gRPC remote service development.  For a video tutorial demonstrating this, please see here.

Saturday, February 06, 2021

gRPC Code Generation using Bndtools and ECF Remote Services

There's a new video tutorial that demonstrates using ECF Remote Services, bndtools, and Eclipse to create an OSGi Remote Service.   

Bndtools has recently added the ability to run code generators as part of a bnd-based project, and with ECF's bndtools workspace template, a single proto3 file added to a project will automatically generate an entire Java remote service API and update/regenerate the API as changes are made to the proto3 file.   No command-line execution of protoc needed.

Further with ECF's project templates, the generated API can be easily implemented and exported as an OSGi Remote Service.

Please watch the video here

Tuesday, December 08, 2020

Using properties to simplify discovery of OSGi Remote Services

OSGi Remote Services are discovered by ECF's Remote Services implementation in two ways:  

1. Via a network discovery protocol provider such as:  Zeroconf, jSLP, etcd, Zookeeper, or some custom protocol

2. Via an xml format known as an Endpoint Description Extender Format (EDEF)

 The EDEF format is specified by the OSGi Remote Service Admin specification.   

When importing an EDEF-defined remote service, it's typically necessary to construct the entire EDEF file 'by hand' rather than having he EDEF generated automatically.  This can be quite complicated to construct by hand as some properties are required, others are optional and it's not obvious what all of the values must be for successful import.

A new capability has been added to ECF's Remote Service Admin implementation that allows EDEF Properties to be used with the EDEF, thus simplifying the creation of remote service consumers that use EDEF for import.

This capability was added to support the usage of JaxRS Remote Services in an Eclipse RCP client.  See a description of this use case here.



Tuesday, July 14, 2020

ECF 3.14.12 released - Now with gRPC for OSGi Remote Services

ECF 3.14.12 was just released

Highlights of this Release

New OSGi Remote Services Distribution provider based upon gRPC/Protocol Buffers. Along with a grpc-osgi-generator project...which allows the generation of a service API from a proto3 service declaration...this provider allows gRPC-based services to be exported and imported as OSGi Remote Services.  This now includes support for unary, server-streaming, and client-streaming gRPC calls.

Enhanced Support for Bndtools-based development of OSGi Remote Services.   The ECF Bndtools Workspace now includes the latest version of ECF Remote Services, along with the gRPC distribution provider, a Hazelcast-based discovery and distribution provider, and project and bndrun templates for creating, running, testing, and debugging OSGi Remote Services in Eclipse+Bndtools 5.


Saturday, August 31, 2019

OSGi Remote Services with Apache Dubbo

ECF's implementation of OSGi R7 Remote Services allows for replacing the underlying distribution system (repsonsible for the object serialization, transport, and other things). 

This makes it relatively easy to replace one kind of distribution (e.g. Jersey, ActiveMQ) with other/new distribution systems. 

Apache Dubbo has recently been contributed to Apache, and we've created a distribution provider based upon Apache Dubbo.

Here's a list of open ECF Remote Service distribution providers.   If you would like Remote Services support for a particular transport, or you've created your own distribution (or discovery) based upon some other transport and wish to make it available to others please let us know.


Monday, February 25, 2019

RESTful OSGi R7 Remote Services with Jersey 2.28 or Apache CXF 3.3

For some time, ECF has had remote service distribution providers that use the Jersey or the CXF implementation of standard Java API for RESTful Web Services (JaxRS). 

These distribution providers allow OSGi R7 Remote Services to be defined via JaxRS annotations and implemented by either Jersey 2.28 or CXF 3.3

OSGi R7 Remote Services provides support for renite service discovery, dynamics, versioning, configuration and extension of the distribution providers, and asynchronous remote calls as well as other features of the OSGi R7 Remote Services and Remote Service Admin specs.

This tutorial shows the use of OSGi Remote Services with these JaxRS distribution providers on Apache Karaf.

There is also a new version of the ECF Bndtools workspace template with example Bndtools projects showing the use of these distribution providers to define, configure, run and deploy RESTful OSGi R7 Remote Services with Bndtools 4.2+.

Sunday, November 04, 2018

ECF 3.14.4 released

ECF 3.14.4 was recently released.  This was a bug-fix release.  There are notes on some of the recent additions here.

Wednesday, August 22, 2018

OSGi Remote Services Between Python and Java

In a previous post, I described the support for OSGi Remote Services and Remote Service Admin in iPOPO 0.8.0 release.   The previous post refers to a tutorial showing a Python service impl and Python consumer.

Python<->Java Distribution Provider

Included with iPOPO 0.8.0 is a distribution provider that allows remote services between Java and Python frameworks.   For example, this is a tutorial, that uses Karaf on the Java side as the remote service implementation, and has a Python consumer that calls the Java-implemented remote service.

Python Service Implementation with Java Consumers

This distribution provider also supports Python-implemented remote services, with Java/OSGi consumers.   With iPOPO for dynamic service injection in Python, and Declarative Services for Java/OSGi, this allows very easy Python<->Java service-level interaction, with support for all dynamics, RSA management agent, extensible/customizable topology management, management of complicated service dependencies, pluggable local and network discovery, and other RS/RSA features handled consistently in both Java and Python.  As well, the use of OSGi-specified EndpointDescription service metadata allows service-level interoperability across languages.

Python<->Java with Protocol Buffers Serialization

Also included with this distribution provider is serialization using Google's protocol buffers.  This allows open, extensible, and efficient rpc between Python and Java.


Tuesday, July 03, 2018

Rest Remote Services with CXF or Jersey

ECF's Photon Release now includes an example of using Karaf with the JaxRS distribution provider.

This distribution provider now fully supports OSGi R7 remote services, including async remote services, using either the Jersey or CXF JaxRS implementations.

This allows service developers to easily use only JAX-RS annotations to define and implement OSGi R7 remote services.

Wednesday, June 20, 2018

ECF Photon supports OSGi R7 Async Services - part 2

In a previous post, I described a usage of OSGi R7's Async Remote Services. This specification makes it easy to define, implement and use non-blocking remote services. ECF's implementation allows the use of pluggable transports...known as distribution providers.

Here's a partial list of distribution providers:

R-OSGi
ECF generic
JMS/ActiveMQ
XML-RPC
Hazelcast
MQTT
Jax-RS Jersey
Jax-RS CXF
JavaGroups
Python.Java (Supports async remote services between Java and Python with protocol buffers serialization)

 It's also straightforward to creation your own distribution provider, using private or legacy transport and/or serialization. This can be done by extending one of the distribution providers above or creating a new one.

Most of these distribution providers have updated examples and/or tutorials, and many of them now have templates included in the Bndtools (4.0+) Support added for Photon.

Separating the remote service contract from the underlying distribution provider via OSGi remote services allows implementers and consumers to create, debug, and test remote services without being bound to a single transport, while still allowing consistent (specified) runtime behavior.

For more info and links, please see the New and Noteworthy.

Tuesday, May 01, 2018

ECF Photon supports OSGi Async Remote Services

In a previous post, I indicated that ECF Photon/3.14.0 will support the recently-approved OSGi R7 specification.   What does this support provide for  developers?

Support osgi.async remote service intent

The OSGi R7 Remote Services specification has been enhanced with remote service intents.  Remote Service Intents allow service authors to specify requirements on the underlying distribution system in a standardized way.   Standardization of service behavior guarantees the same runtime behavior across distribution providers and implementations.

The osgi.async intent allows the service interface to use return types such as Java8's CompletableFuture or OSGi's Promise.   With a supporting distribution provider, the proxy will automatically implement the asynchronous/non-blocking behavior for the service consumer.

For example, consider a service interface:
public interface Hello {
    CompletableFuture<String> hello(String greetingMessage);
}
When an implementation of this service is registered and exported as a remote service with the osgi.async intent:
@Component(property = { "service.exported.interfaces=*", "service.intents=osgi.async" })
public class HelloImpl implements Hello {
    public CompletableFuture<String> hello(String greetingMessage) {
          CompletableFuture<String> future = new CompletableFuture<String>();
          future.complete("Hi.  This a response to the greeting: "+greetingMessage);
          return future;
    }
}
Then when a Hello service consumer (on same or other process) discovers, imports and then remote service is injected by DS:
@Component(immediate=true)
public class HelloConsumer {

    @Reference
    private Hello helloService;

    @Activate
    void activate() throws Exception {
        // Call helloService.hello remote service without blocking
        helloService.hello("hi there").whenComplete((result,exception) -> {
            if (exception != null)
                exception.printStackTrace(exception);
            else
                System.out.println("hello service responds: " + result);
        });
    }
}
The injected helloService instance (a distribution-provider-constructed proxy) will automatically implement the asynchronous remote call.   Since the proxy is constructed by the distribution provider, there is no need for the consumer to implement anything other than calling the 'hello' method and handling the response via the Java8-provided whenComplete method.   Java8's CompletionStage, Future, and OSGi's Promise are also supported return types.  (Only the return type is used to identify asynchronous remote methods, any method name can be used).  For example: the following signature is also supported as an async remote service:
public interface Hello {
    org.osgi.util.promise.Promise<String> hello(String greetingMessage);
}

Further, OSGi R7 Remote Services supports a timeout property:
@Component(property = { "service.exported.interfaces=*", "service.intents=osgi.async", "osgi.basic.timeout=20000" })
public class HelloImpl implements Hello {
    public CompletableFuture<String> hello(String greetingMessage) {
          CompletableFuture<String> future = new CompletableFuture<String>();
          future.complete("Hi.  This a response to the greeting: "+greetingMessage);
          return future;
    }
}
With ECF's RSA implementation and distribution providers, this timeout will be honored by the underlying distribution system. That is, if the remote implementation does not return within 20000ms, then the returned CompletableFuture will complete with a TimeoutException.

Async Remote Services make it very easy for service developers to define, implement, and consume loosely-coupled and dynamic asynchronous remote services.   It also makes asynchronous remote service contracts transport independent, allowing the swapping of distribution providers or creating/using custom providers without changes to the service contract.

For the documented example code, see here

Monday, April 23, 2018

ECF Photon adds Gogo Commands

A third major enhancement for ECF's implementation of OSGi Remote Services is the addition of Apache Gogo console commands for examining the existing state of remote services, and the ability to export a service and import an endpoint from the OSGi console.

See this wiki page describing the new commands and their usage.