MCP For Claude Marketplace
Forefront

Forefront MCP Connector for Claude

A+

Access Forefront AI models directly from your agent — generate chat completions, manage fine-tuning jobs, and collect LLM outputs with pipelines.

10 tools Official Updated Jun 28, 2026 Official Vinkius Partner
More Details Connect to Claude

Connect your Forefront account to any AI agent to harness powerful language models, manage custom fine-tuning, and orchestrate data pipelines directly through natural conversation.

What you can do

  • Chat & Text Completions — Generate high-quality model responses using chat-ml format or standard prompts via create_chat_completion and create_completion.
  • Fine-Tuning Management — Kick off custom training jobs on base models with your own training and validation datasets using create_fine_tune.
  • Pipeline Orchestration — Create and manage pipelines to collect LLM outputs, track samples, and organize metadata using create_pipeline, list_pipelines, get_pipeline, and add_pipeline_data.

How it works

  1. Subscribe to this server
  2. Enter your Forefront API Key
  3. Start generating text and managing pipelines from Claude, Cursor, or any MCP client
llmfine-tuningtext-generationpipelinesai-models

10 tools expose this connector's capabilities to your AI agent.

add_pipeline_data

Add data samples to a pipeline

list_pipelines

Returns a list of your pipelines

create_chat_completion

Pass messages array in chat-ml format. Creates a model response for the given chat conversation

create_completion

Pass a single prompt string. Creates a completion response for a given prompt

create_fine_tune

Creates a fine-tuning job

create_pipeline_dataset

Create a dataset from a pipeline selection

create_pipeline

Create a new pipeline to collect LLM outputs

get_pipeline_count

Get count of pipeline selection

get_pipeline_samples

Get data samples for a pipeline selection

get_pipeline

Returns a pipeline object by ID

See how to talk to your AI agent using Forefront.

Generate a chat completion with model 'forefront-llm' asking 'What is the capital of France?'

I will call `create_chat_completion` with model 'forefront-llm' and the message 'What is the capital of France?'. The model responded: 'The capital of France is Paris.'

List all my active pipelines on Forefront.

I will query your pipelines using `list_pipelines`. I found 2 active pipelines: 'customer-feedback-pipeline' (ID: pipe_123) and 'qa-testing-pipeline' (ID: pipe_456).

Create a new pipeline named 'production-logs'.

I will call `create_pipeline` with the name 'production-logs'. The pipeline has been successfully created with ID 'pipe_789'.

You can use the `create_chat_completion` tool. Provide the model name and an array of messages in chat-ml format to receive the generated response.

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