Memory Journal MCP Server

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

🧠 Stop Experiencing AI Amnesia

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.

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Experience true context-aware development:

• "Why did we choose SQLite over Postgres for this service last month?" (Semantic search)
• "Run the /issue-triage workflow on the top priority ticket in the Kanban board." (GitHub operations)
• "Who has been touching the auth module recently, and what's our team collaboration density?" (Team analytics)
• "I'm stuck on this database error. Raise a 'blocker' flag for @sarah so her agent sees it next session." (Hush Protocol)
• "Close issue #42 and log an entry explaining our architectural fix for the parsing bug." (Context lifecycles)
• "Draw a visual graph showing how my last 10 architectural decisions relate to each other." (Knowledge graph)

See complete examples & prompts →

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🎯 What Sets Us Apart

70 MCP Tools · 17 Workflow Prompts · 36 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, Hush Protocol Flags)

---

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, system prompts, 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. ACKNOWLEDGE FLAGS: If the briefing JSON contains activeFlags (count > 0), you MUST print an alert ABOVE the table: ⚠️ **{count} active flag(s)** — review before proceeding. followed by each flag (🚩 {flag_type} → @{target_user}: {preview}).
4. RENDER TABLE: Parse the remaining JSON into a dense 2-column Markdown Table (Field, Value).
   • RESTRICTION: NO bulleted lists inside the table. Do NOT truncate summaries or issues.
   • FORMATTING: Group related properties (use <br> for line breaks).
   • REQUIRED GROUPS: GitHub (Repo, Branch, CI, PRs, Insights), Issues, Entry Counts, Latest Entries/Summaries, Analytics, Milestones, Workspaces.
5. STOP & WAIT: Do NOT autonomously resume past tasks or start work on new issues mentioned in the session summary. The briefing is strictly for context.

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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 →

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📋 Core Capabilities

🛠️ 70 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 →

📡 36 Resources (27 Static + 9 Template)

Static Resources (appear in resource lists):

• memory://briefing - Session initialization: compact context for AI agents (~300 tokens) — includes localTime and optional activeFlags
• 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 operational telemetry log (requires AUDIT_LOG_PATH)
• memory://flags - Active (unresolved) team flags dashboard (requires TEAM_DB_PATH)
• memory://flags/vocabulary - Configured flag vocabulary terms

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

• 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
• memory://briefing/{repo} - Context targeted to a specific repository

Note: The memory://github/status, memory://github/insights, memory://github/milestones, and memory://milestones/{number} resources also accept an optional /{repo} path suffix for cross-repo targeting.

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⚡ Code Mode: Maximum Efficiency (90% Token Savings)

Code Mode (mj_execute_code) is a revolutionary approach that dramatically reduces token usage by up to 90% and is included by default in all presets. Instead of spending thousands of tokens on sequential tool calls, AI agents use a single sandboxed execution to reason faster.

Code executes in a worker_threads sandbox designed as a secure multi-tenant process isolation environment. 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.team.passTeamFlag())
• 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 69 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"]
}

---

🤫 Hush Protocol: Asynchronous Team Collaboration

The Hush Protocol reimagines team collaboration for AI-augmented workflows by replacing noisy Slack/Teams messages with structured, machine-actionable flags.

When you encounter a blocker, need a review, or want to broadcast a milestone, your AI agent can raise a flag in the shared Team Database:

• Actionable Visibility: Active flags automatically surface at the very top of the memory://briefing payload for all team members. When another developer's agent starts a session, it immediately sees your blockers and can help resolve them autonomously.
• Structured Types: Raise specific flag types (blocker, needs_review, help_requested, fyi). You can customize your team's vocabulary via the --flag-vocabulary configuration.
• Searchable History: Unlike chat messages that disappear into the void, Hush flags are permanent, query-able AI journal entries. Your agents can search past needs_review flags to understand how architectural blockers were conquered.

Dashboard & Operations: Read memory://flags to see an active dashboard overview and use mj.team.passTeamFlag() / mj.team.resolveTeamFlag() to manage them programmatically in Code Mode.

Complete Hush Protocol guide and Mermaid sequence diagrams →

---

🚀 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}}",
        "ALLOWED_IO_ROOTS": "/path/to/your/git/repo"
      }
    }
  }
}

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}}",
        "ALLOWED_IO_ROOTS": "/path/to/repo,/path/to/other,/path/to/your/skills",
        "AUTO_REBUILD_INDEX": "true",
        "MEMORY_JOURNAL_MCP_TOOL_FILTER": "codemode",
        "CODEMODE_INTERNAL_FULL_ACCESS": "true",
        "BRIEFING_ENTRY_COUNT": "3",
        "BRIEFING_SUMMARY_COUNT": "1",
        "BRIEFING_INCLUDE_TEAM": "true",
        "BRIEFING_ISSUE_COUNT": "3",
        "BRIEFING_PR_COUNT": "3",
        "BRIEFING_PR_STATUS": "true",
        "BRIEFING_WORKFLOW_COUNT": "3",
        "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",
        "AUDIT_LOG_PATH": "/path/to/your/mcp-audit.jsonl",
        "TEAM_AUTHOR": "your_username"
      }
    }
  }
}

💡 Tip: Optimize your context window! Journal entries (BRIEFING_ENTRY_COUNT) capture frequent, granular actions (e.g. bug fixes, implementation steps). Session summaries (BRIEFING_SUMMARY_COUNT) surface high-level retrospectives meant to pass strategic context continuously across distinct AI sessions. Use both appropriately to keep the agent briefing highly focused!

Variants (modify the config above):

Restart your MCP client and start journaling!

Option 3: HTTP/SSE Transport (Remote Access)

🔒 Security Posture: Stdio vs HTTP

• Stdio (Default): Runs implicitly within the secure boundaries of your local IDE or command-line environment. No explicit authentication is required because the execution context is already trusted.
• HTTP/SSE: Exposes the server over a network socket. By default, HTTP binds ONLY to localhost and blocks wildcard CORS to prevent unauthorized access and CSRF attacks. Public network binding (--server-host 0.0.0.0) requires explicit authentication (--auth-token or --oauth-enabled). The server will throw a fatal error if you attempt to expose it publicly without securing it.

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) and enable the automated proactive analytics scheduler (e.g. daily digest), you MUST provide an authentication token:

export MCP_AUTH_TOKEN="your_secure_random_token"
memory-journal-mcp --transport http --port 3000 --server-host 0.0.0.0 --digest-interval 1440

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.

Documentation truncated — see the full README on GitHub.