Memory Journal MCP Server

🎯 AI Context + Project Intelligence: Bridge disconnected AI sessions with persistent project memory and automatic session handoff — with full GitHub workflow integration.

GitHub • Wiki • Changelog • Release Article

🚀 Quick Deploy:

• npm Package - npm install -g memory-journal-mcp
• Docker Hub - Alpine-based with full semantic search

🎯 What This Does

What Sets Us Apart

65 MCP Tools · 17 Workflow Prompts · 38 Resources · 10 Tool Groups · Code Mode · GitHub Commander (Issue Triage, PR Review, Milestone Sprints, Security/Quality/Perf Audits) · GitHub Integration (Issues, PRs, Actions, Kanban, Milestones, Insights) · Team Collaboration (Shared DB, Vector Search, Cross-Project Insights)

🎯 Why Memory Journal?

When managing large projects with AI assistance, you face a critical challenge:

• Thread Amnesia - Each new AI conversation starts from zero, unaware of previous work
• Lost Context - Decisions, implementations, and learnings scattered across disconnected threads
• Repeated Work - AI suggests solutions you've already tried or abandoned
• Context Overload - Manually copying project history into every new conversation

Memory Journal solves this by acting as your project's long-term memory, bridging the gap between fragmented AI sessions.

Ask Agent naturally:

• "Show me my recent journal entries"
• "Create a backup of my journal"
• "Check the server health status"
• "Find entries related to performance"

See complete examples & prompts →

flowchart TB
    subgraph Session["🤖 AI Session Start"]
        Briefing["📋 Read Briefing<br/>(memory://briefing)"]
    end

    subgraph Core["📝 Journal Operations"]
        Create["Create Entry"]
        Retrieve["Retrieve & Search"]
        Link["Link Entries"]
    end

    subgraph Search["🔍 Hybrid Search"]
        FTS["Keyword (FTS5)"]
        Semantic["Semantic (Vector)"]
        DateRange["Date Range"]
        RRF["Reciprocal Rank Fusion"]
    end

    subgraph GitHub["🐙 GitHub Integration"]
        Issues["Issues & Milestones"]
        PRs["Pull Requests"]
        Actions["GitHub Actions"]
        Kanban["Kanban Boards"]
        Insights["Repository Insights"]
    end

    subgraph Outputs["📊 Outputs"]
        Reports["Standups & Retrospectives"]
        Graphs["Knowledge Graphs"]
        Timeline["Project Timelines"]
    end

    Session --> Core
    Core --> Search
    Core <--> GitHub
    Search --> Outputs
    GitHub --> Outputs

Suggested Rule (Add to AGENTS.md, GEMINI.md, etc):

🛑 MANDATORY SESSION START ROUTINE

Execute BEFORE fulfilling any user request in a new session:

1. TARGET: Infer repo_name from the active workspace context or user prompt. If the task is not associated with a specific project, fallback to using the generic resource without a repo name (which defaults to the first registered workspace).
2. FETCH: Use the MCP read_resource tool (Server: memory-journal-mcp) to read memory://briefing/{repo_name} (or memory://briefing if falling back).
   • RESTRICTION: Do NOT use execute_code for this step.
3. RENDER TABLE: Extract userMessage and output it EXCLUSIVELY as a vertical Markdown Table (2 columns: Field and Value).
   • RESTRICTION: NO bulleted lists. NO truncation of arrays or lists.
   • REQUIRED MAP: Output all data comprehensively. Map these fields to the "Field" column:
     • Application / Project
     • Journal Entries
     • Team DB Entries
     • Latest Entry (Journal)
     • Latest Entry (Team)
     • GitHub (Include Repo, Branch, CI Status, Issues, PRs, Insights on separate lines in the Value column)
     • Milestone Progress
     • Template Resources (Output count only, not URLs)
     • Registered Workspaces (Output FULL list of project names)
     • Available Extensions (Rules, Skills, Workflows)

Tool Filtering

[!IMPORTANT] All shortcuts and tool groups include Code Mode (mj_execute_code) by default for token-efficient operations. To exclude it, add -codemode to your filter: --tool-filter starter,-codemode

Control which tools are exposed via MEMORY_JOURNAL_MCP_TOOL_FILTER (or CLI: --tool-filter):

Filter Syntax: shortcut or group or tool_name (whitelist mode) · -group (disable group) · -tool (disable tool) · +tool (re-enable after group disable)

Custom Selection: List individual tool names to create your own whitelist: --tool-filter "create_entry,search_entries,semantic_search"

Groups: core, search, analytics, relationships, io, admin, github, backup, team, codemode

Complete tool filtering guide →

📋 Core Capabilities

🛠️ 65 MCP Tools (10 Groups)

Complete tools reference →

🎯 17 Workflow Prompts

• find-related - Discover connected entries via semantic similarity
• prepare-standup - Daily standup summaries
• prepare-retro - Sprint retrospectives
• weekly-digest - Day-by-day weekly summaries
• analyze-period - Deep period analysis with insights
• goal-tracker - Milestone and achievement tracking
• get-context-bundle - Project context with Git/GitHub/Kanban
• get-recent-entries - Formatted recent entries
• project-status-summary - GitHub Project status reports
• pr-summary - Pull request journal activity summary
• code-review-prep - Comprehensive PR review preparation
• pr-retrospective - Completed PR analysis with learnings
• actions-failure-digest - CI/CD failure analysis
• project-milestone-tracker - Milestone progress tracking
• confirm-briefing - Acknowledge session context to user
• session-summary - Create a session summary entry with accomplishments, pending items, and next-session context
• team-session-summary - Create a retrospective team session summary entry securely isolated to the team database

Complete prompts guide →

📡 38 Resources (25 Static + 13 Template)

Static Resources (appear in resource lists):

• memory://briefing / memory://briefing/{repo} - Session initialization: compact context for AI agents (~300 tokens)
• memory://instructions - Behavioral guidance: complete server instructions for AI agents
• memory://recent - 10 most recent entries
• memory://significant - Significant milestones and breakthroughs
• memory://graph/recent - Live Mermaid diagram of recent relationships
• memory://health - Server health & diagnostics
• memory://graph/actions - CI/CD narrative graph
• memory://actions/recent - Recent workflow runs
• memory://tags - All tags with usage counts
• memory://statistics - Journal statistics
• memory://rules - User rules file content for agent awareness
• memory://workflows - Available agent workflows summary
• memory://skills - Agent skills index (names, paths, excerpts)
• memory://github/status - GitHub repository status overview
• memory://github/insights - Repository stars, forks, and 14-day traffic summary
• memory://github/milestones - Open milestones with completion percentages
• memory://team/recent - Recent team entries with author attribution
• memory://team/statistics - Team entry counts, types, and author breakdown
• memory://help - Tool group index with descriptions and tool counts
• memory://help/gotchas - Field notes, edge cases, and critical usage patterns
• memory://metrics/summary - Aggregate tool call metrics since server start (calls, errors, token estimates, duration) — HIGH priority
• memory://metrics/tokens - Per-tool token usage breakdown sorted by output token cost — MEDIUM priority
• memory://metrics/system - Process-level metrics: memory (MB), uptime (s), Node.js version, platform — MEDIUM priority
• memory://metrics/users - Per-user call counts (populated when OAuth user identifiers are present) — LOW priority
• memory://audit - Last 50 write/admin tool call entries from the JSONL audit log (requires AUDIT_LOG_PATH)

Template Resources (require parameters, fetch directly by URI):

• memory://github/status/{repo} - Repository status targeted by repo
• memory://github/insights/{repo} - Repository insights targeted by repo
• memory://github/milestones/{repo} - Open milestones targeted by repo
• memory://milestones/{repo}/{number} - Milestone detail targeted by repo
• memory://projects/{number}/timeline - Project activity timeline
• memory://issues/{issue_number}/entries - Entries linked to issue
• memory://prs/{pr_number}/entries - Entries linked to PR
• memory://prs/{pr_number}/timeline - Combined PR + journal timeline
• memory://kanban/{project_number} - GitHub Project Kanban board
• memory://kanban/{project_number}/diagram - Kanban Mermaid visualization
• memory://milestones/{number} - Milestone detail with completion progress
• memory://help/{group} - Per-group tool reference with parameters and annotations

Code Mode: Maximum Efficiency

Code Mode (mj_execute_code) dramatically reduces token usage (70–90%) and is included by default in all presets.

Code executes in a sandboxed VM context with multiple layers of security. All mj.* API calls execute against the journal within the sandbox, providing:

• Static code validation — blocked patterns include require(), process, eval(), and filesystem access
• Rate limiting — 60 executions per minute per client
• Hard timeouts — configurable execution limit (default 30s)
• Full API access — all 10 tool groups are available via mj.* (e.g., mj.core.createEntry(), mj.search.searchEntries(), mj.github.getGithubIssues(), mj.analytics.getStatistics())
• Strict Readonly Contract — Calling any mutation method under --tool-filter readonly safely halts the sandbox to prevent execution, returning a structured { success: false, error: "..." } response to the agent instead of a raw MCP protocol exception.

⚡ Code Mode Only (Maximum Token Savings)

Run with only Code Mode enabled — a single tool that provides access to all 65 tools' worth of capability through the mj.* API:

{
  "mcpServers": {
    "memory-journal-mcp": {
      "command": "memory-journal-mcp",
      "args": ["--tool-filter", "codemode"]
    }
  }
}

This exposes just mj_execute_code. The agent writes JavaScript against the typed mj.* SDK — composing operations across all 10 tool groups and returning exactly the data it needs — in one execution. This mirrors the Code Mode pattern pioneered by Cloudflare for their entire API: fixed token cost regardless of how many capabilities exist.

Disabling Code Mode

If you prefer individual tool calls, exclude codemode:

{
  "args": ["--tool-filter", "starter,-codemode"]
}

🚀 Quick Start

Option 1: npm (Recommended)

npm install -g memory-journal-mcp

Option 2: From Source

git clone https://github.com/neverinfamous/memory-journal-mcp.git
cd memory-journal-mcp
npm install
npm run build

Add to MCP Config

Add this to your ~/.cursor/mcp.json, Claude Desktop config, or equivalent:

Basic Configuration

{
  "mcpServers": {
    "memory-journal-mcp": {
      "command": "memory-journal-mcp",
      "env": {
        "GITHUB_TOKEN": "ghp_your_token_here",
        "PROJECT_REGISTRY": "{\"my-repo\":{\"path\":\"/path/to/your/git/repo\",\"project_number\":1}}"
      }
    }
  }
}

Advanced Configuration (Recommended)

Showcasing the full power of the server, including Multi-Project Routing, Team Collaboration, Copilot awareness, and Context Injections.

{
  "mcpServers": {
    "memory-journal-mcp": {
      "command": "memory-journal-mcp",
      "env": {
        "DB_PATH": "/path/to/your/memory_journal.db",
        "TEAM_DB_PATH": "/path/to/shared/team.db",
        "GITHUB_TOKEN": "ghp_your_token_here",
        "PROJECT_REGISTRY": "{\"my-repo\":{\"path\":\"/path/to/repo\",\"project_number\":1},\"other-repo\":{\"path\":\"/path/to/other\",\"project_number\":5}}",
        "AUTO_REBUILD_INDEX": "true",
        "MEMORY_JOURNAL_MCP_TOOL_FILTER": "codemode",
        "BRIEFING_ENTRY_COUNT": "3",
        "BRIEFING_INCLUDE_TEAM": "true",
        "BRIEFING_ISSUE_COUNT": "1",
        "BRIEFING_PR_COUNT": "1",
        "BRIEFING_PR_STATUS": "true",
        "BRIEFING_WORKFLOW_COUNT": "1",
        "BRIEFING_WORKFLOW_STATUS": "true",
        "BRIEFING_COPILOT_REVIEWS": "true",
        "RULES_FILE_PATH": "/path/to/your/RULES.md",
        "SKILLS_DIR_PATH": "/path/to/your/skills",
        "MEMORY_JOURNAL_WORKFLOW_SUMMARY": "/deploy: prod deployment | /audit: security scan"
      }
    }
  }
}

Variants (modify the config above):

Restart your MCP client and start journaling!

Option 3: HTTP/SSE Transport (Remote Access)

For remote access or web-based clients, run the server in HTTP mode:

memory-journal-mcp --transport http --port 3000

To bind to all interfaces (required for containers):

memory-journal-mcp --transport http --port 3000 --server-host 0.0.0.0

Endpoints:

Session Management: The server uses stateful sessions by default. Include the mcp-session-id header (returned from initialization) in subsequent requests.

• OAuth 2.1 — RFC 9728/8414, JWT/JWKS, granular scopes (opt-in via --oauth-enabled)
• 7 Security Headers — CSP, HSTS (opt-in), X-Frame-Options, and more
• Rate Limiting — 100 req/min per IP · CORS — configurable multi-origin (exact-match) · 1MB body limit
• Server Timeouts — Request (120s), keep-alive (65s), headers (66s) · 404 handler · Cross-protocol guard
• Build Provenance · SBOM · Supply Chain Attestations · Non-root execution

Example with curl:

Initialize session (returns mcp-session-id header):

curl -X POST http://localhost:3000/mcp \
  -H "Content-Type: application/json" \
  -H "Accept: application/json, text/event-stream" \
  -d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-03-26","capabilities":{},"clientInfo":{"name":"test","version":"1.0"}}}'

List tools (with session):

curl -X POST http://localhost:3000/mcp \
  -H "Content-Type: application/json" \
  -H "Accept: application/json, text/event-stream" \
  -H "mcp-session-id: YOUR_SESSION_ID" \
  -d '{"jsonrpc":"2.0","id":2,"method":"tools/list","params":{}}'

Stateless Mode (Serverless)

For serverless deployments (Lambda, Workers, Vercel), use stateless mode:

memory-journal-mcp --transport http --port 3000 --stateless

Automated Scheduling (HTTP Only)

When running in HTTP/SSE mode, enable periodic maintenance jobs with CLI flags. These jobs run in-process on setInterval — no external cron needed.

Note: These flags are ignored for stdio transport because stdio sessions are short-lived (tied to your IDE session). For stdio, use OS-level scheduling (Task Scheduler, cron) or run the backup/cleanup tools manually.

memory-journal-mcp --transport http --port 3000 \
  --backup-interval 60 --keep-backups 10 \
  --vacuum-interval 1440 \
  --rebuild-index-interval 720

Each job is error-isolated — a failure in one job won't affect the others. Scheduler status (last run, result, next run) is visible via memory://health.

GitHub Integration Configuration

The GitHub tools (get_github_issues, get_github_prs, etc.) auto-detect the repository from your git context when PROJECT_REGISTRY is configured or the MCP server is run inside a git repository.

Multi-Project Workflows: For agents to seamlessly support multiple projects, provide PROJECT_REGISTRY.

Dynamic Context Resolution & Auto-Detection

When executing GitHub tools (issues, PRs, context, etc.), the server resolves repository context in this order:

1. Dynamic Project Routing: If the agent passes a repo string that matches a key in your PROJECT_REGISTRY, the server dynamically mounts the physical directory mapped to that project. It executes git commands locally and automatically infers the owner.
2. Explicit Override: If the agent provides both owner and repo explicitly, those values override auto-detection for API calls.
3. Missing Context: Without PROJECT_REGISTRY or explicit parameters, the server blocks execution and returns {requiresUserInput: true} to prompt the agent.

Automatic Project Routing (Kanban / Issues)

When opening an issue or viewing/moving a Kanban card, the server needs a GitHub Project number. It determines this via:

1. Exploring the raw project_number argument passed by the agent.
2. Checking if the repo string precisely matches an entry in your PROJECT_REGISTRY, seamlessly mapping it to its pre-configured project_number.
3. Falling back to the globally defined DEFAULT_PROJECT_NUMBER if set.

🔐 OAuth 2.1 Authentication

For production deployments, enable OAuth 2.1 authentication on the HTTP transport:

Supported Scopes:

Quick Start:

memory-journal-mcp --transport http --port 3000 \
  --oauth-enabled \
  --oauth-issuer https://auth.example.com/realms/mcp \
  --oauth-audience memory-journal-mcp \
  --oauth-jwks-uri https://auth.example.com/realms/mcp/protocol/openid-connect/certs

Or via environment variables:

export OAUTH_ENABLED=true
export OAUTH_ISSUER=https://auth.example.com/realms/mcp
export OAUTH_AUDIENCE=memory-journal-mcp
memory-journal-mcp --transport http --port 3000

Note: OAuth is opt-in. When not enabled, the server falls back to simple token authentication via MCP_AUTH_TOKEN environment variable, or runs without authentication.

🔄 Session Management

1. Session start → agent reads memory://briefing (or memory://briefing/{repo}) and shows project context
2. Session summary → use /session-summary to capture progress and next-session context
3. Next session's briefing includes the previous summary — context flows seamlessly

🔧 Configuration

GitHub Integration (Optional)

export GITHUB_TOKEN="your_token"              # For Projects/Issues/PRs

Scopes: repo, project, read:org (org-level project discovery only)

GitHub Management Capabilities

Memory Journal provides a hybrid approach to GitHub management:

MCP Server Tools (Read + Kanban + Milestones + Issue Lifecycle):

• get_github_issues / get_github_issue - Query issues
• get_github_prs / get_github_pr - Query pull requests
• get_github_context - Full repository context
• get_kanban_board / move_kanban_item - Kanban management
• get_github_milestones / get_github_milestone - Milestone tracking with completion %
• create_github_milestone / update_github_milestone / delete_github_milestone - Milestone CRUD
• get_repo_insights - Repository traffic & analytics (stars, clones, views, referrers, popular paths)
• create_github_issue_with_entry / close_github_issue_with_entry - Issue lifecycle with journal linking

Why this design? The MCP server focuses on value-added features that integrate journal entries with GitHub (Kanban views, Milestones, timeline resources, context linking). Standard GitHub mutations (create/close issues, merge PRs, manage releases) are handled directly by agents via gh CLI.

Complete GitHub integration guide →

🏗️ Architecture

Data Flow

flowchart TB
    AI["🤖 AI Agent<br/>(Cursor, Windsurf, Claude)"]

    subgraph MCP["Memory Journal MCP Server"]
        Tools["🛠️ 65 Tools"]
        Resources["📡 38 Resources"]
        Prompts["💬 17 Prompts"]
    end

    subgraph Storage["Persistence Layer"]
        SQLite[("💾 SQLite<br/>Entries, Tags, Relationships")]
        Vector[("🔍 Vector Index<br/>Semantic Embeddings")]
        Backups["📦 Backups"]
    end

    subgraph External["External Integrations"]
        GitHub["🐙 GitHub API<br/>Issues, PRs, Actions"]
        Kanban["📋 Projects v2<br/>Kanban Boards"]
    end

    AI <-->|"MCP Protocol"| MCP
    Tools --> Storage
    Tools --> External
    Resources --> Storage
    Resources --> External

Stack

┌─────────────────────────────────────────────────────────────┐
│ MCP Server Layer (TypeScript)                               │
│  ┌─────────────────┐  ┌─────────────────┐  ┌─────────────┐  │
│  │ Tools (65)      │  │ Resources (38)  │  │ Prompts (17)│  │
│  │ with Annotations│  │ with Annotations│  │             │  │
│  └─────────────────┘  └─────────────────┘  └─────────────┘  │
├─────────────────────────────────────────────────────────────┤
│ Native SQLite Engine                                        │
│  ┌─────────────────┐  ┌─────────────────┐  ┌─────────────┐  │
│  │ better-sqlite3  │  │ sqlite-vec      │  │ transformers│  │
│  │ (High-Perf I/O) │  │ (Vector Index)  │  │ (Embeddings)│  │
│  └─────────────────┘  └─────────────────┘  └─────────────┘  │
├─────────────────────────────────────────────────────────────┤
│ SQLite Database with Hybrid Search                          │
│  ┌─────────────────────────────────────────────────────────┐│
│  │ entries + tags + relationships + embeddings + backups   ││
│  └─────────────────────────────────────────────────────────┘│
└─────────────────────────────────────────────────────────────┘

🔧 Technical Highlights

Performance & Portability

• TypeScript + Native SQLite - High-performance better-sqlite3 with synchronous I/O
• sqlite-vec - Vector similarity search via SQLite extension
• @huggingface/transformers - ML embeddings in JavaScript
• Lazy loading - ML models load on first use, not startup

Performance Benchmarks

Memory Journal is designed for extremely low overhead during AI task execution. We include a vitest bench suite to maintain these baseline guarantees:

• Database Reads: Operations execute in fractions of a millisecond. calculateImportance is ~13-14x faster than retrieving 50 recent entries.
• Vector Search Engine: Both search (~140-220 ops/sec) and indexing (~1600-1900+ ops/sec) are high-throughput via sqlite-vec with SQL-native KNN queries.
• Core MCP Routines: getTools uses cached O(1) dispatch (~4800-7000x faster than get_recent_entries). create_entry and search_entries execute through the full MCP layer with sub-millisecond overhead.

To run the benchmarking suite locally:

npm run bench

Testing

Extensively tested across two frameworks:

npm test          # Unit + integration tests
npm run test:e2e  # End-to-end HTTP/SSE transport tests

Security

• Deterministic error handling - Every tool returns structured {success, error, code, category, suggestion, recoverable} responses with actionable context — no raw exceptions, no silent failures, no misleading messages
• Local-first - All data stored locally, no external API calls (except optional GitHub)
• Input validation - Zod schemas, content size limits, SQL injection prevention
• Path traversal protection - Backup filenames validated
• MCP 2025-03-26 annotations - Behavioral hints (readOnlyHint, destructiveHint, etc.)
• HTTP transport hardening - 7 security headers, configurable multi-origin CORS, 1MB body limit, built-in rate limiting (100 req/min), server timeouts, HSTS (opt-in), 30-min session timeout, 404 handler, cross-protocol guard
• Token scrubbing - GitHub tokens and credentials automatically redacted from error logs

Data & Privacy

• Single SQLite file - You own your data
• Portable - Move your .db file anywhere
• Soft delete - Entries can be recovered
• Auto-backup on restore - Never lose data accidentally

📚 Documentation & Resources

• GitHub Wiki - Complete documentation
• Copilot Setup Guide - Cross-agent memory bridge between IDE agents and GitHub Copilot
• Docker Hub - Container images
• npm Package - Node.js distribution
• Issues - Bug reports & feature requests

📄 License

MIT License - See LICENSE file for details.

🤝 Contributing

Built by developers, for developers. PRs welcome! See CONTRIBUTING.md for guidelines.

Migrating from v2.x? Your existing database is fully compatible. The TypeScript version uses the same schema and data format.