# Project Oracle

> Use this tool when you need to manage and track the context and history of AI agent interactions, enabling more informed and personalized responses. Project Oracle solves problems related to information retention and recall, allowing agents to learn from previous experiences and adapt to changing situations. It accepts input from AI agents and outputs relevant context and history, ideal for use cases requiring continuity and memory, such as conversational dialogue systems and interactive storytelling.

Canonical page: https://skillsregistry.net/skills/mikelane-project-oracle  
JSON: https://api.skillsregistry.net/v1/skills/mikelane-project-oracle

## Description

A stateful MCP server that remembers what your AI agent has already seen.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/l7kyzch8r6)
- **Repository:** <https://github.com/mikelane/project-oracle>

## 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": "mikelane-project-oracle"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/mikelane-project-oracle` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/mikelane-project-oracle/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