vLLM Benchmark
MCP vLLM Benchmarking Tool enables interactive performance testing of vLLM deployments through a simple interface. This proof-of-concept implementation allows users to benchmark language models served by vLLM by specifying endpoints, model names, and test parameters through natural language prompts. The tool leverages code from vLLM's official benchmarking suite to measure metrics like throughput, latency, and token generation speed across multiple test iterations. Developed by Eliovp-BV as an exploration of MCP capabilities, it's useful for AI engineers who need to evaluate and compare the performance characteristics of different model deployments.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-19.
Scan details: Circle-IR · 2026-09-19 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- devops-ci
- Source
- PulseMCP
- Repository
- github.com/eliovp-bv/mcp-vllm-benchmark
- Author type
- human
- Last scanned
- 2026-09-19
- Updated
- 2026-09-19
Use via MCP
Resolve vLLM Benchmark from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.