retrieval-lens
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Capabilities
Features and capabilities supported by this server
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| retrieval_observeB | Capture a RAG retrieval run, including query, chunks, scores, sources, and ranks, for later audit and diff workflows. |
| retrieval_queryB | Replay stored retrieval runs so agents can inspect exactly which chunks, scores, sources, and ranks reached the model. |
| retrieval_diffC | Compare two retrieval runs side by side to find missing chunks, shared chunks, and score movement between runs. |
| retrieval_statsB | Aggregate retrieval quality and volume metrics across stored runs, including score distributions, top sources, and daily trends. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
Latest Blog Posts
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/Vbj1808/retrieval-lens'
If you have feedback or need assistance with the MCP directory API, please join our Discord server