# Aquifer

> Use this tool when you need to manage unpredictable traffic patterns in distributed systems, particularly those involving autonomous agents. Aquifer provides a runtime environment for handling spiky agentic traffic in Golang, solving problems related to scalability and reliability. It takes in agentic traffic as input and outputs optimized traffic management, ideal for use cases requiring efficient handling of variable workloads.

Canonical page: https://skillsregistry.net/skills/rjpruitt16-aquifer  
JSON: https://api.skillsregistry.net/v1/skills/rjpruitt16-aquifer

## Description

A MCP Runtime for dealing with spiky agentic traffic in golang

## Trust

- **Trust score (0–1):** 0.64
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/enyzczg81a)
- **Repository:** <https://github.com/rjpruitt16/aquifer>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "rjpruitt16-aquifer"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/rjpruitt16-aquifer` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/rjpruitt16-aquifer/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt