
Memory Journal Mcp
io.github.neverinfamous由 GitHub 账号 neverinfamous 发布v1.1.3更新于 Oct 24, 2026
Developer journal with knowledge graphs, relationships, Git context, and semantic search
发布方自己的服务:Memory.fit
概览
一个本地开发者日志服务器,让助手记录条目、建立知识图谱关系,并结合 Git 与 GitHub 上下文进行语义检索。
- 可以做什么
- 提供基于 SQLite 的日志,包含条目创建、更新、删除与标签工具,文本与日期范围搜索、语义/向量搜索、统计与跨项目洞察,以及关系链接和图谱可视化。还提供 GitHub 工具,用于议题、拉取请求、里程碑、看板和 CI 工作流上下文,并支持 JSON 与 Markdown 导入导出、备份恢复和团队数据库模式。沙箱化的 Code Mode 工具可运行 JavaScript 调用 mj.* API,在一次调用中组合多项操作。
- 适用场景
- 适合希望助手跨会话保存持久工作记录、回忆过往决策与里程碑,并把 Git 或 GitHub 议题与拉取请求上下文带入摘要、站会、回顾和代码评审准备的开发者。
- 运行要求
- 以本地进程方式通过 stdio 运行(npm 包、源码构建或 Docker 镜像),也可选用 HTTP/SSE。npm 与源码方式需要 Node.js。可选环境变量包括 DB_PATH、TEAM_DB_PATH、TEAM_AUTHOR、GITHUB_TOKEN、PROJECT_REGISTRY、ALLOWED_IO_ROOTS、AUDIT_LOG_PATH、RULES_FILE_PATH、SKILLS_DIR_PATH、MCP_AUTH_TOKEN 及 OAuth 相关设置;GitHub 功能需要令牌和网络访问。
安装
在 SourceWeft 中
- 打开 控制台中的 Memory Journal Mcp,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
README
Memory Journal MCP Server
[GitHub] [npm] [Docker Pulls] [License: MIT] [Status] [MCP Registry] [Security] [GitHub Stars] [TypeScript] [Coverage] [E2E] [Tests] [Benchmarks] [CI]
📚 Full Documentation (Wiki) • Changelog • Security • Release Article
[!TIP] Value Proposition Bridge disconnected AI sessions seamlessly. Enable persistent project memory instantly. Automate handoffs with robust GitHub integration. Eliminate AI amnesia today.
🚀 Quick Deploy:
- npm Package -
npm install -g memory-journal-mcp(orpnpm add -g memory-journal-mcp) - Docker Hub - Alpine-based with full semantic search
🧠 Eliminate AI Amnesia
Large projects face a critical challenge. You lose context between sessions.
- Stop Thread Amnesia - AI conversations start fresh. They ignore previous work.
- Retain Deep Context - Decisions and code scatter across threads; Memory Journal preserves them automatically.
- End Repeated Work - AI repeats failed solutions; persistent history tracks every prior attempt.
- Prevent Context Overload - Manual history copying wastes tokens; dynamic briefings deliver targeted context automatically.
Memory Journal builds your project's long-term memory. It acts as a Project Context Graph for AI-assisted engineering. It bridges human workflows (Issues, PRs, Kanban, Milestones) with agent execution (Git, tests, decisions).
Experience true context-aware development:
- "Why did we choose SQLite over Postgres for this service last month?" (Semantic search)
- "Run the
/issue-commander(triageworkflow) 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)
- "Commit the changes and automatically generate a structured journal entry using the `--journal` wrapper flag." (Automated lifecycles)
- "Draw a visual graph showing how my last 10 architectural decisions relate to each other." (Knowledge graph)
Comprehensive access to internal state via resources (memory://briefing, memory://workflows, memory://rules, memory://health, memory://help, memory://staleness, GitHub status/milestones, team stats, and metrics/latency). Dynamic repo variants also support cross-repo targeting (like memory://briefing/{+repo} or memory://kanban/{+repo}/{project_number}). Resources documentation →
🎯 What Sets Us Apart
MCP Tools · Workflow Prompts · Resources · 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)
Isolate Environments with Multi-Tenancy
Memory Journal supports multi-tenancy out of the box via the workspace_id construct, acting as a strict isolation barrier for multiple journals sharing the same SQLite database file.
- Auto-Resolution: When
workspace_idis omitted, the server automatically resolves the target workspace. It matchesproject_numberagainstPROJECT_REGISTRY, checks content/tag keyword aliases, or inspectsprocess.cwd()before falling back toDEFAULT_WORKSPACE_ID(default:default). - Data Partitioning & Cross-Workspace Queries: Core CRUD, Soft-Delete/Restore, FTS5 Search, Vector Semantic Search (
semantic_search), and Analytics tools enforceworkspace_idisolation end-to-end. Read and search tools acceptworkspace_id: "*"to query across all workspaces. External write and mutation paths reject wildcard overrides. - Immutability & Controlled Migration: Entries receive a
workspace_idupon creation that standard updates cannot overwrite directly. To migrate an entry across workspaces, callupdate_entrywithworkspace_id: "*"andtarget_workspace_id. - Server Config: Set
--default-workspace-id(or theDEFAULT_WORKSPACE_IDenvironment variable) to configure the default fallback workspace for the server instance. This lets you run multiple isolated journal interfaces on a single physical database.
Suggested Rule (Add to AGENTS.md, GEMINI.md, system prompts, etc.)
View Session Initialization Routine
🛑 Session Initialization Routine
When the user initializes the session context by executing the load-briefing prompt:
- You will receive the output of the
memory://briefing/{repo_name}resource. - Prepend your response EXACTLY as:
📋 Briefing loaded —
{repo_name}{paste ENTIRE briefing here} - Address the user's request below the briefing.
- NEVER autonomously execute tasks listed in the briefing.
- Do NOT proactively ask the user to load the briefing. Wait for them to use the prompt.
Control Access with Tool Filtering
[!IMPORTANT] All shortcuts and tool groups always include Code Mode (
mj_execute_code) and Runtime Configuration (update_configuration) as escape-hatch tools so agents can never lock themselves out of the configuration system or Code Mode.
Control which tools are exposed using any of the 3 configuration sources (precedence: CLI flag > environment variable > config file):
- CLI flag:
--tool-filter <filter> - Environment variable:
MEMORY_JOURNAL_MCP_TOOL_FILTER(Note:TOOL_FILTERis only a fallback display variable in the session briefing and does not activate tool filtering on its own) memory-journal.config.{yaml,yml,json}key:"toolFilter"
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, git, backup, team, codemode
Complete tool filtering guide →
📋 Unlock Core Capabilities
🛠️ MCP Tools
🎯 Workflow Prompts
Specialized workflow prompts cover session briefing, standup & retro prep, goal tracking, PR & issue command, session summaries, and journal optimization. Additional prompts support CMS REM supervision, adversarial plan reviews, code & security audits, secure commit workflows, and anti-hallucination healing. Complete prompts guide →
📡 Resources
See the Complete resources guide → for the full list of dynamic context resources, including memory://briefing, memory://instructions, GitHub integration endpoints, telemetry metrics, and templated views.
- Dynamic Resource Templates: Resources
memory://briefing/{+repo},memory://agent-context/{+repo},memory://agent-id/{+repo},memory://actions/recent/{+repo},memory://github/status/{+repo},memory://github/milestones/{+repo},memory://milestones/{+repo}/{number}, andmemory://kanban/{+repo}/{project_number}accept an RFC 6570{+repo}path parameter for targeted project context.
⚡ Code Mode: Maximum Efficiency (90% Token Savings)
Code Mode (mj_execute_code) 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 pre-warmed worker_threads V8 isolate pool + secondary vm.createContext boundary designed as a secure multi-tenant process isolation environment. All mj.* API calls execute against the journal within the sandbox, providing:
- V8 code generation restrictions —
eval()andFunction()construction from strings disabled at the V8 engine level viacodeGeneration: { strings: false, wasm: false } - Frozen prototypes & cross-realm constructor lockdown — all built-in prototypes (
Object,Function,Array,Error, etc.) andmj.*API bindings are frozen, and.constructoris neutered acrossObject,Function,AsyncFunction,GeneratorFunction, andAsyncGeneratorFunctionprototypes in both the innervmrealm and outer worker realm to prevent dynamic constructor chain escapes - Single-pass lexical validation — pre-validation rate-limiting and 50KB byte caps run before any code normalization, followed by a single-pass lexical comment/string scanner (preserving
${...}template expressions) and static rules blockingrequire(),import(),process,eval(),Reflect.*,Symbol.*,Object.getPrototypeOf/setPrototypeOf/defineProperty,new Proxy(), and filesystem/network access - Proxy constructor nullified —
Proxy: undefinedin the sandbox prevents meta-object protocol abuse - Prototype-safe RPC allowlist — host-side
Object.hasOwn()validation, recursion-bounded argument normalization, and--tool-filterenforcement prevent workers from invoking unauthorized or filtered API methods - Rate limiting — 60 executions per minute per client
- Hard timeouts — configurable execution limit (default 30s) with bounded async timer tracking (
setTimeout/sleepcapped and cleared on completion) - Egress boundary enforcement — result serialization capped (default 100KB via
CODE_MODE_MAX_RESULT_SIZE) with automatic payload compaction to prevent OOM via oversized payloads - Full API access — all tool groups are available via
mj.*(e.g.,mj.core.createEntry(),mj.search.searchEntries(),mj.github.getGithubIssues()) - Strict Readonly Contract — Calling any mutation method under
--tool-filter readonlysafely 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 Minimal Surface (Maximum Token Savings)
Run with the codemode filter and --codemode-internal-full-access to expose only the escape-hatch tools (mj_execute_code and update_configuration) on the MCP tool list while retaining full internal access to the mj.* API inside the sandbox:
This exposes only mj_execute_code and update_configuration to the client's tools/list, reducing tool schema overhead to the minimum while preserving full programmatic capability via mj.*. The agent writes JavaScript against the typed mj.* SDK — composing operations across all 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. Without --codemode-internal-full-access (or CODEMODE_INTERNAL_FULL_ACCESS=true), internal mj.* methods are scoped to the active --tool-filter.
🚀 Quick Start & Deployment
Note: Configuration is resolved using strict precedence: CLI flags > Environment Variables > Config File > Defaults.
🛠️ Debugging Configuration: Run
memory-journal-mcp --dump-config(or pass--dump-configas an arg) to print the fully resolved configuration payload with automatically redacted secrets. This is the primary method for diagnosing overriding issues.
Configure Basics Quickly
💡 Tip: Don't want to manually escape JSON strings for
PROJECT_REGISTRY? Runnpx memory-journal-mcp project create <name> --path <repo-path> [--number <project-number>]in your terminal to automatically bootstrap and update your MCP configuration!
Power Up with Advanced Configuration
Showcasing the full power of the server, including Multi-Project Routing, Team Collaboration, Copilot awareness, and Context Injections.
💡 Tip: Use
npx memory-journal-mcp project create <name> --path <repo-path> [--number <project-number>]to easily configure multiple repositories into yourPROJECT_REGISTRYwithout manual JSON escaping!
💡 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!
📋 Customizing the Session Briefing
The memory://briefing resource is dynamically assembled at each session start to provide rich, token-efficient ambient context. By default, it automatically surfaces:
- System State: Server version, capability statuses, resource/tool counts, test health, and
memory://metrics/summarybreadcrumbs. - Repository Context: Git working tree status, unreleased changes, exact code-map paths, and prioritized gatekeeper CI workflows.
- Ambient Context: Active workspace paths, local time, analytics.
You control exactly what additional content your agent sees across three dimensions:
Context Injections: Set RULES_FILE_PATH and SKILLS_DIR_PATH to surface user rules and agent skills as companion resources (memory://rules, memory://skills) alongside the briefing.
Repo Targeting: In multi-repo setups, agents read memory://briefing/{+repo} to get a briefing scoped to a specific repository registered in PROJECT_REGISTRY.
Briefing Presets (click to expand)
Minimal (fast sessions) — Reduce briefing to bare essentials for quick interactions:
Full Context (onboarding agents) — Maximize context for agents unfamiliar with the project:
DevOps-Heavy — Emphasize CI/CD and GitHub state for infrastructure workflows:
Full briefing customization guide →
Variants (modify the config above):
Restart your MCP client and start journaling!
Connect Remotely with HTTP/SSE Transport
[!IMPORTANT] Security Posture: Stdio vs HTTP (Fail-Closed Startup Guards)
- 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 (
ALLOWED_IO_ROOTSdefaults to fail-closed[]unless configured).- HTTP/SSE (
--transport http): Exposes the server over a network socket and enforces three fail-closed startup guards:
- Mandatory Filesystem Boundary (
ALLOWED_IO_ROOTS/--allowed-io-roots): Always required in HTTP mode so filesystem boundaries are explicitly declared.- Mandatory Public Authentication: By default, HTTP binds ONLY to
localhostand blocks wildcard CORS to prevent unauthorized access and CSRF attacks. Binding to a non-loopback address (--server-host 0.0.0.0) requires explicit authentication (MCP_AUTH_TOKEN/--auth-tokenor--oauth-enabled).- Mandatory Public Origin for Non-Loopback OAuth (
PUBLIC_ORIGIN/--public-origin): When--oauth-enabledis bound to a non-loopback address,--public-origin(PUBLIC_ORIGIN) is strictly required so RFC 9728 Protected Resource Metadata cannot be spoofed viaHostheaders.
For remote access or web-based clients, run the server in HTTP mode:
To bind to all interfaces (required for containers) and enable the automated proactive analytics scheduler (e.g. daily digest), you MUST provide both ALLOWED_IO_ROOTS and an authentication token:
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) - Comprehensive Security Headers — CSP, HSTS (opt-in), X-Frame-Options, and more
- Rate Limiting — 100 req/min per subject/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):
List tools (with session):
Stateless Mode (Serverless)
For serverless deployments (Lambda, Workers, Vercel), use stateless mode:
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.
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.
Integrate Seamlessly with GitHub
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, configure your PROJECT_REGISTRY (tip: use npx memory-journal-mcp project create <name> --path <repo-path> [--number <project-number>]).
Dynamic Context Resolution & Auto-Detection
When executing GitHub tools (issues, PRs, context, etc.), the server resolves repository context in this order:
- Dynamic Project Routing: If the agent passes a
repostring that matches a key in yourPROJECT_REGISTRY, the server dynamically mounts the physical directory mapped to that project. It executes git commands locally and automatically infers theowner. - Explicit Override: If the agent provides both
ownerandrepoexplicitly, those values override auto-detection for API calls. - Missing Context: Without
PROJECT_REGISTRYor explicit parameters, the server blocks execution and returns{requiresUserInput: true}to prompt the agent. If an agent encounters this blocked state, it can seamlessly recover by invoking themj.admin.registerProject()method via Code Mode to auto-configure the project registry on the fly.
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:
- Exploring the raw
project_numberargument passed by the agent. - Checking if the
repostring precisely matches an entry in yourPROJECT_REGISTRY, seamlessly mapping it to its pre-configuredproject_number. - Falling back to the globally defined
DEFAULT_PROJECT_NUMBERif set.
🔐 OAuth 2.1 Authentication
For production deployments, enable OAuth 2.1 authentication on the HTTP transport:
Supported Scopes:
Quick Start:
Or via environment variables:
Note: OAuth is opt-in. When not enabled, the server falls back to simple token authentication via
MCP_AUTH_TOKENenvironment variable, or runs without authentication.
🔄 Session Management
- Session start → agent reads
memory://briefing(ormemory://briefing/{repo}) and shows project context - Session summary → use
/session-summaryto capture progress and next-session context - Next session's briefing includes the previous summary — context flows seamlessly
🔧 Configuration
Environment Variables
GitHub Integration (Optional)
Scopes: repo, project, read:org (org-level project discovery only)
Manage GitHub Seamlessly
Memory Journal provides a hybrid approach to GitHub management:
MCP Server Tools (Read + Kanban + Milestones + Issue Lifecycle):
See the Complete tools reference for all supported GitHub integration capabilities, including query commands, Kanban management, milestone tracking, analytics, and issue lifecycle events.
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
ghCLI.
Complete GitHub integration guide →
Automate with GitHub Commander Workflows
The server natively bundles the memory-journal-mcp agent skill (served via SEP-2640 and memory://skills). It also provides built-in issue-commander, pr-commander, and cms-rem-supervisor MCP workflow prompts for autonomous DevOps stewardship: Issue Triage, Milestone Sprints, PR Reviews, Copilot Audits, Security Audits, Code Quality Audits, Performance Audits, Roadmap Kickoffs, and Dependency Updates. These workflows enforce multi-gate validation (lint, typecheck, test, and security checks) locally during agent tasks.
🏗️ Architecture
Data Flow
Stack
🔧 Technical Highlights
Performance & Portability
- TypeScript + Native SQLite - High-performance
better-sqlite3with synchronous I/O - sqlite-vec - Vector similarity search via SQLite extension
- @huggingface/transformers - Local ML embedding models in JavaScript
- Background Warmup - Model weights (~23MB) are loaded into memory asynchronously on server startup to avoid first-request latency. If the server is invoked before warmup completes, the first semantic search or vector insertion will incur a network-bound cold start (~1.5s - 3s) while the weights are cached locally.
Performance Benchmarks
Memory Journal is designed for extremely low overhead during AI task execution. We include a vitest bench suite across database, vector search, and MCP server routines to maintain these baseline guarantees:
- Database Operations (
sqlite-adapter.bench.ts):calculateImportanceruns at ~51,600 ops/sec (~0.03ms mean, ~27x faster than retrieving 50 recent entries) via a 256-entry LRU prepared statement cache.getRecentEntries (limit 50)executes at ~1,870 ops/sec (~0.63ms mean),updateEntryat ~2,380 ops/sec (~0.79ms mean),createEntryat ~1,060 ops/sec (~1.69ms mean), andsearchEntries(FTS5 BM25 + batch importance hydration) at ~176 ops/sec (~6.2ms mean). - Vector Search Engine (
vector-search.bench.ts): Both k-NN similarity search (~1,050 ops/sec, ~1.8ms mean with batch entry hydration) and vector indexing (~4,220 ops/sec, ~0.41ms mean) are high-throughput viasqlite-vec(vec0withchunk_size=256). - Core MCP Routines (
mcp-server.bench.ts):getToolsuses cached O(1) dispatch (~7.2M–9.4M ops/sec, ~0.0001ms). Full end-to-endcallToolinvocations (including interceptor, token estimation, and project registry resolution) run at ~1,775 ops/sec (~0.65ms) forget_recent_entries, ~205 ops/sec (~5.4ms) forsearch_entries, and ~800 ops/sec (~2.4ms) forcreate_entry.
To run the benchmarking suite locally:
Testing
Extensively tested across two frameworks:
Security
Note: When updating schemas or validation logic, please refer to the
/zodskill for best practices on Standard Schema and Safe Parsing.
- 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, and
<untrusted_remote_content>prompt-injection boundary tagging - Path traversal & SSRF protection -
ALLOWED_IO_ROOTSsandbox containment with URL-decode/symlink verification, backup path validation, and outbound webhook DNS/IP SSRF blocking - Multi-tenant & filter enforcement - End-to-end
workspace_idisolation across SQLite and Vector search, plus execution-layer--tool-filterenforcement acrosstools/call, Code Mode (mj.*), and fallback handlers - MCP 2025-11-25 annotations & icons - Behavioral hints (
readOnlyHint,destructiveHint, etc.) and capability icons - HTTP transport hardening - OAuth 2.1
tokenClaimspropagation, principal-bound stateful sessions (100max active sessions), comprehensive security headers, configurable multi-origin CORS, 1MB body/stream limit, built-in per-subject/IP rate limiting (100 req/min), server timeouts, HSTS (opt-in), 30-min session timeout, and localhost-bound metrics (METRICS_EXPORT=prometheusautomatically starts the standalone metrics server on127.0.0.1:9465, customizable viaMJ_METRICS_PORTandMJ_METRICS_HOST, in addition to mounting/metricson the HTTP transport) - Token scrubbing - GitHub tokens and credentials automatically redacted from error and audit logs
Data & Privacy
- Single SQLite file - You own your data
- Portable - Move your
.dbfile 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
- Deployment Guide - CI/CD pipeline, environments, and version bump checklist
- 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! Ensure all unit and E2E tests, linting, and typechecks pass. See CONTRIBUTING.md for guidelines.
Upgrading from an earlier version? Your existing SQLite database is automatically migrated on startup.
来源:README.md,提交 81f98e4
工具
0版本历史
1- v1.1.3最新Sep 16, 2026
评分
已满足适用检查项的 50%
该评分衡量此收录条目的完整程度,依据注册中心条目、端点与公开来源计算得出。它不是对服务器本身的评价,也不表示服务器安全或当前可用:可连通性是带日期的检查结果,评分也不包含安装量或用户评价。
- 近 30 天内可连通25 分
请保持端点能够响应 MCP 握手;SourceWeft 每 30 天探测一次。
- 已声明认证方式10 分
请在注册中心条目中声明凭据请求头,或保持端点能够响应探测,以便判定其认证方式。
- 已列出工具15 分
请让服务器在无凭据时响应 tools/list,或发布可在沙箱中无凭据启动的软件包。
- 描述必需15 分
- 图标10 分
- 文档15 分
- 许可证10 分
其他 Memory 集成

Memory.fit
fit.memory官方发布者
托管式 Memory.fit 服务器,让 AI 读取你的训练、睡眠、恢复与饮食数据,并写回每周计划、每日目标和饮食计划。
pg.ddx.io: the PostgreSQL community's memory
io.ddx.pg官方发布者
pg.ddx.io: the PostgreSQL community's memory 的托管 MCP 服务,由 pg.ddx.io 发布;无需登录;Streamable HTTP;29 个工具。
var.gg Naming Memory
gg.var官方发布者
远程 MCP 服务器,可根据领域概念推荐并检索韩、日、中、越、英多语言的代码标识符名称,并提供 ERD 结构查询。

Counterparts
ai.counterparts
面向 Claude Code 与 Claude Desktop 的本地优先长期记忆:助手自行写下关于你和项目的笔记,并在之后的会话中回忆起来。

LAHZE - Persian AI Memory Platform
由 GitHub 账号 pedramgholizadeh 发布
以波斯语为先的地理记忆平台:发现地点,起草并发布仅限波斯语的记忆。AI 翻译