Spanly
Spanly is a dedicated observability and monitoring platform for Model Context Protocol (MCP) servers. It captures every tool call, prompt, and resource request flowing through MCP traffic, providing real-time dashboards with metrics on traces, sessions, errors, and durations. Spanly requires no code changes and works with any language, integrating seamlessly alongside existing monitoring tools like Datadog, Sentry, or New Relic. The platform includes a free tier with no credit card required and an open-source SDK and CLI for agent deployment. Engineering teams can quickly identify performance bottlenecks, debug errors, and analyze client usage patterns across multiple servers and environments.
- Category
- Large Language Models (LLMs)
- Pricing
- Free
Problem solved
MCP servers lack specialized observability, making it difficult to monitor tool interactions, diagnose errors, and optimize performance. Spanly fills this gap by offering out-of-the-box monitoring tailored to MCP, enabling teams to maintain reliable AI tool chains.
Use cases
- Monitor MCP server performance and latency
- Debug tool call and prompt errors
- Track client connections and session details
- Analyze resource request patterns
- Identify slow operations and bottlenecks
- Compare metrics across staging and production environments
Audience
- Developers
- ML Engineers
- Startups
- Enterprise
Pros
- No code changes required for integration
- Free tier available with no credit card
- Supports any MCP server language
- Detailed dashboards with traces, sessions, and errors
- Open-source SDK and CLI
Cons
- Limited to MCP traffic only, not general observability
- Relatively new platform, ecosystem still growing
- Requires running an agent on each server
- May lack advanced alerting compared to established tools
Official website: https://www.spanly.com/
Canonical LambdaBase page: https://www.lambdabase.com/tools/spanly