🧠 Memory MCP Server - Orchestrator

- Conversation history with full context storage
- Version‑controlled dynamic context storage
- Knowledge graph for entity relationship management
- Vector embeddings for semantic search
- AI‑powered planning with hierarchical tasks and dependencies
- Google Gemini integration for prompt refinement, summarization, and more
- Tavily web search integration
- Data validation, logging, backup, and restore

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| Requirement | Version | Required |
|------------|---------|----------|
| Node.js | 18.x or higher | ✅ |
| npm | Latest | ✅ |
| Git | Any | ✅ |

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npm install
npm run test

The server requires API keys for external services. These should be configured in your MCP client settings.

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| Service | Environment Variable | Required | Get API Key |
|---------|---------------------|----------|-------------|
| Google Gemini | GEMINI_API_KEY | ✅ | Get Key |
| Tavily Search | TAVILY_API_KEY | ✅ | Get Key |

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npm install
<details>

<summary><b>Example 1: Creating an AI-Generated Plan</b></summary>

// 2. Create a plan from the refined prompt
const plan = await create_task_plan({
agent_id: "my-agent",
refined_prompt_id: refinedPrompt.refined_prompt_id
});

// 3. Get AI suggestions for subtasks
const subtasks = await ai_suggest_subtasks({
agent_id: "my-agent",
plan_id: plan.plan_id,
parent_task_id: plan.task_ids[0]
});

</details>

<details>

<summary><b>Example 2: Knowledge Graph Operations</b></summary>

// Query with natural language
const results = await kg_nl_query({
agent_id: "my-agent",
query: "What classes handle user operations?"
});
```

</details>

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The server provides 65+ tools organized into categories:

<details>
<summary><b>Conversation Management (4 tools)</b></summary>

- store_conversation_message - Store messages in conversation history
- get_conversation_history - Retrieve past conversations
- search_conversation_by_keywords - Search conversations by keywords
- summarize_conversation - AI-powered conversation summarization

</details>

<details>
<summary><b>Context Management (9 tools)</b></summary>

- store_context - Store dynamic contextual data
- get_context - Retrieve stored context
- get_all_contexts - Get all contexts for an agent
- search_context_by_keywords - Keyword search in contexts
- prune_old_context - Clean up old context entries
- summarize_context - AI summarization of context
- extract_entities - Extract entities from context
- semantic_search_context - Vector-based semantic search

</details>

<details>
<summary><b>Plan Management (15 tools)</b></summary>

- create_task_plan - Create plans (manual or AI-generated)
- get_task_plan_details - Get detailed plan information
- list_task_plans - List all plans
- update_task_plan_status - Update plan status
- delete_task_plan - Remove plans
- ai_analyze_plan - AI analysis of plan quality
- ai_suggest_subtasks - AI-generated subtask suggestions
- ai_suggest_task_details - AI-enhanced task details
- ai_summarize_task_progress - AI progress summaries

</details>

<details>
<summary><b>Knowledge Graph (9 operations)</b></summary>

- knowledge_graph_memory - Comprehensive KG operations
- Create/read/update/delete entities
- Manage relationships
- Add observations
- Natural language queries
- Infer relationships
- Generate visualizations

</details>

<details>
<summary><b>Comprehensive Logging (23 tools)</b></summary>

- Tool execution logging
- Task progress tracking
- Error logging and management
- Correction tracking
- Success metrics
- Review logs (task and plan level)

</details>

<details>
<summary><b>Git Operations (16 tools)</b></summary>

- Complete Git workflow support
- Clone, pull, push, commit
- Branch management
- Stash operations
- Remote management

</details>

<details>
<summary><b>External Services (5 tools)</b></summary>

- tavily_web_search - Advanced web search
- ask_gemini - Direct Gemini AI queries
- analyze_code_file_with_gemini - AI code analysis
- refine_user_prompt - AI prompt enhancement
- ingest_codebase_embeddings - Vector embedding generation

</details>

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