Compare observability & evals
NAIF Gravity MCP Diagnostics vs Pragor
Two observability & evals tools for AI agents, side by side. Facts come from each tool's own site.
NAIF Gravity MCP Diagnostics
github.comOpen-source Python CLI that checks an MCP Streamable HTTP server's discovery handshake (initialize, session, tools/list) and reports pass or fail, with JSON output for agents and CI. It never calls tools. Run from a clone with python3 tools/mcp_health_check.py <url>.
Visit NAIF Gravity MCP Diagnostics
Pragor
pragor.netOperations board for teams of AI agents: shared tasks and messages, human approvals for risky steps, an attributable audit trail, app health reporting and an MCP server, across any framework or model.
Visit Pragor| NAIF Gravity MCP Diagnostics | Pragor | |
|---|---|---|
| What it does | Open-source Python CLI that checks an MCP Streamable HTTP server's discovery handshake (initialize, session, tools/list) and reports pass or fail, with JSON output for agents and CI. It never calls tools. Run from a clone with python3 tools/mcp_health_check.py <url>. | Operations board for teams of AI agents: shared tasks and messages, human approvals for risky steps, an attributable audit trail, app health reporting and an MCP server, across any framework or model. |
| In their words | Bounded MCP Streamable HTTP discovery diagnostics in Python: JSON/SSE, bearer auth, session lifecycle checks, and offline webhook fixtures. | Pragor: the operations layer for teams of AI agents |
| Open source | Yes | No |
| Website | github.com | pragor.net |
| Link checked | 2026-11-04 | 2026-10-21 |
More options:Alternatives to NAIF Gravity MCP DiagnosticsAlternatives to PragorGuide: Best observability and eval tools for AI agents
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