# Institutional Memory Agent MCP Server

> Use this tool when you need to leverage collective knowledge and experience of security operations center (SOC) analysts to inform AI-driven decision-making. It enables AI agents to query and record analyst reasoning via a knowledge graph, providing access to institutional memory from Splunk. This tool is ideal for use cases where retaining and applying historical security insights is crucial, such as incident response and threat hunting.

Canonical page: https://skillsregistry.net/skills/shiwani42-mike  
JSON: https://api.skillsregistry.net/v1/skills/shiwani42-mike

## Description

Enables AI agents to query and record SOC analyst reasoning via a knowledge graph, allowing access to institutional memory from Splunk.

## Trust

- **Trust score (0–1):** 0.58
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/p2vz5uvtxy)
- **Repository:** <https://github.com/shiwani42/Mike>

## 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": "shiwani42-mike"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/shiwani42-mike` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/shiwani42-mike/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