Build teams of AI agents that collaborate, automate workflows, and complete complex tasks together.
PromptShuttle
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About PromptShuttle
PromptShuttle provides an OpenAI-compatible API and web dashboard designed for developers and B2B teams that require server-side multi-agent orchestration without embedding agent logic directly into application code. The platform enables users to define agent flows in the dashboard and execute them through a standard chat completions endpoint, which spawns sub-agents, handles tool calls, and returns an aggregated final result in a single API call. It supports proxying to multiple LLM providers, allowing teams to route each agent to different models across providers such as OpenAI, Anthropic, Google, and DeepSeek without modifying application code beyond base URL configuration. PromptShuttle includes built-in observability features, including visualization of agent execution graphs, per-step timing and cost breakdowns, and usage tracking with budgets per tenant and per flow. The tool also offers team workflow capabilities such as reusable prompt templates, structured prompting, context engineering, and result comparison across models, along with collaboration features for deployed applications. It operates as an API rather than an SDK framework, enabling teams to update agents and routing logic via configuration instead of redeploying code. Additionally, PromptShuttle supports the Model Context Protocol (MCP), allowing MCP-compatible clients to manage flows and prompts through a hosted MCP server endpoint. The platform follows a freemium pricing model, with a free tier available for basic usage and paid plans for advanced features and higher limits.
Key features
- OpenAI-compatible API for multi-agent orchestration
- Proxy routing across multiple LLM providers
- Server-side execution without embedding agent logic
- Visualization of agent execution graphs
- Per-step timing and cost breakdowns
- Usage tracking with budgets per tenant and flow
- Reusable prompt templates and structured prompting
- Result comparison across models
- MCP server endpoint support
- Team collaboration features for deployed applications
Use cases
- Training AI models with multi-agent workflows
- Building scalable agentic applications for B2B teams
- Centralizing logs and cost tracking for AI operations
Pros
- Eliminates embedding agent logic into application code by handling orchestration server-side
- Supports multi-provider routing across OpenAI, Anthropic, Google, DeepSeek, and others without code changes
- Provides built-in observability with agent execution graphs, per-step cost breakdowns, and usage tracking
- Offers multi-tenant isolation for teams or clients with isolated billing and flow configurations
- Includes Model Context Protocol (MCP) support for managing flows and prompts via MCP-compatible clients
Cons
- Requires configuration updates rather than code changes to modify agent flows
- May introduce latency due to server-side orchestration and multi-agent routing
- Limited customization compared to SDK-based frameworks for highly specialized agent logic
Frequently asked questions about PromptShuttle
What is PromptShuttle and how does it work?
PromptShuttle is an OpenAI-compatible API and web dashboard that orchestrates multi-agent workflows server-side. Users send a standard chat completions API call, and PromptShuttle handles sub-agent spawning, tool calls, provider routing, and returns a final aggregated result without embedding agent logic into the application code.
Who should use PromptShuttle?
PromptShuttle is designed for platform teams, agencies, and businesses that need to deploy AI agent capabilities without requiring each team to learn an agent framework. It suits legacy software integration, background job automation, and multi-tenant environments.
Does PromptShuttle support multiple LLM providers?
Yes, PromptShuttle allows routing each agent to different models across providers such as OpenAI, Anthropic, Google, and DeepSeek without modifying application code beyond base URL configuration.
How does PromptShuttle handle cost tracking and budgets?
PromptShuttle provides built-in cost tracking with aggregated costs across the entire agent tree, per-step cost breakdowns, and the ability to set budgets per tenant or per flow.
Can PromptShuttle integrate with MCP-compatible clients?
Yes, PromptShuttle supports the Model Context Protocol (MCP) and exposes a hosted MCP server endpoint, allowing clients like Claude Desktop or Cursor to manage flows, prompts, and analytics through natural language.
What is the pricing model for PromptShuttle?
PromptShuttle follows a freemium pricing model with a free tier for basic usage and paid plans for advanced features and higher limits. Pricing is usage-based with no additional agent orchestration surcharges.
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