Trinity Memory MCP Server
Allows PostgreSQL as a storage backend for the Trinity memory system, enabling persistent memory storage and retrieval.
Allows SQLite as a storage backend for the Trinity memory system, enabling local persistent memory storage.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Trinity Memory MCP Serverremember that user prefers dark mode"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Trinity — Open Memory Layer with Governance
v8.2.1 — 治理优先的记忆操作系统:模型会换、框架会换,但记忆不换。 Trinity 是让记忆可迁移、可治理、可交易的基础设施。
🚀 开源就绪(2026-08-26):MIT 许可证 · 数据全本地(无遥测)· 存储加密 + 审计可证明 · 全部基准带可复现 manifest。详见 docs/BENCHMARK_GUIDE.md(复现指南)、 docs/PRIVACY.md(隐私说明)、docs/INDEX.md(文档索引)。
🏆 官方基准(2026-08-27):LongMemEval-S(ICLR 2025 官方集,500 问) Session Recall@10 = 0.98-0.99 · Turn Recall@10 = 0.93-0.94 · QA accuracy 0.358(旧口径)/ 0.467(升级口径:top-3 完整上下文 + 语义 judge,300 问) ——检索对齐头部(TiMem/Mem0 0.9+);结果带 manifest 完全可复现。
🧠 自进化认知协作平台(2026-08-29):八大能力在线——记忆(加密+审计+版本链)、 知识层(198 源)、自进化引擎(记忆/系统/代码三类指标)、自动化编排(8 规则+全编排)、 AgentMesh 协作(委托+订阅+配额)、记忆资产化、联邦同步、RAG 服务化(/v1/retrieval)。 代码自改三级达成(参数/脚本/自动合入,fulltest 门禁保障)。 快速接入见 docs/QUICKSTART_20260829.md · 完整总览见 docs/TRINITY_SUMMARY_20260827.md · 优化报告见 docs/OPTIMIZATION_REPORT_20260827.md。
Quick Start
# 安装(本地运行,无遥测)
pip install -e ".[dev,test]"
# 启动 API(:8001)+ MCP(:8000/:8003)
python -m trinity.api.server --port 8001
python -m trinity.mcp.server --mode sse --port 8000
# 写入与检索
python -m trinity ingest --content "用户偏好暗色模式"
python -m trinity search --query "用户偏好" --top-k 5
# 维护(每日链:health/evolution/decay/tiers/sync/backup...)
powershell -File dsh-ops/trinity-dsh-maintenance.ps1 -Tasks all
# 评测(12 项功能断言 + 官方基准复现)
python scripts/run_evals.py --all
python benchmark/longmemeval_official_runner.py --limit 100 --qa --out results.jsonTrinity is not a "memory library." It is a Memory Operating System — an infrastructure layer that any memory store (vector DB, graph DB, SQLite) can plug into, with retrieval, governance, identity, evolution, and economic protocols on top.
定位(2026-08-15, V2):记忆是 AI 最后的切换成本。Trinity = 开放记忆层 + 治理底座—— 记忆可进可出(可迁移标准)、企业敢存(治理/合规/审计)、 记忆值钱(TrustExchange 市场)。
Related MCP server: Strata Memory MCP Server
Architecture
┌──────────────────────────────────────────────────────────┐
│ Agent Layer A2A v0.3 · DSH 原生 · 共享聚合池 · 身份 │
├──────────────────────────────────────────────────────────┤
│ Governance Layer RBAC(6) · 50-Guardian · 审计签名 · 加密 │
│ B3 策略层(isolated/shared/delegated) │
├──────────────────────────────────────────────────────────┤
│ Memory Layer 47 通道 · PPR · 意图压缩 · 蒸馏 11x │
│ 个性化(PAHF) · 跨模态 · 联邦 │
├──────────────────────────────────────────────────────────┤
│ Storage Layer SQLite(FTS5) · PostgreSQL · AES-GCM 加密 │
├──────────────────────────────────────────────────────────┤
│ Economic Layer TrustExchange 记忆市场 · 资产定价 │
└──────────────────────────────────────────────────────────┘528 Python files · 206K+ lines · 147 API endpoints · 815 tests passing
Quick Start
# 安装(系统 Python 3.11+)
cd trinity
pip install -e .
# 验证
python -c "import trinity; print(trinity.__version__)" # → 8.2.1
# 全量测试(815 passed / 50 skipped / 0 failed,系统 Python 3.14)
python -m pytest tests/ -q服务(全在线,supervisor 自愈)
服务 | 端口 | 说明 |
trinity-api | :8001 | REST(147 端点) |
trinity-mcp | :8000 / :8003 | MCP SSE / MCP v2 streamable-http |
gateway | :8002 | OpenAI/Mem0 兼容层(DeepSeek 上游,鉴权/限流/模型映射) |
dashboard | :3005 | 可视化 |
PostgreSQL | :5430 | 维护镜像(docker) |
Key Features(名实一致,2026-08-15 实测)
能力 | 状态 | 说明 |
41 个 active 模块 | ✅ | 运行路径可达(另有 261 个论文对齐储备, |
47 通道检索 | ✅ | BM25+jieba / FAISS HNSW / Exabase / BEAM-LIGHT / Hindsight / PPR 图扩散 / RRF 融合 |
语义缓存 | ✅ | Redis 305x,scope 隔离 |
存储加密 | ✅ | AES-256-GCM 可选(TRINITY_STORAGE_ENCRYPTION),FTS/哈希链兼容 |
治理策略层 | ✅ | B3:YAML 策略(isolated/shared/delegated)+ 热切换 + 审计 |
多智能体 | ✅ | A2A v0.3 + 共享聚合池 + 身份漂移检测 |
意图压缩 | ✅ | SimpleMem 对齐(TRINITY_INTENT_CLUSTER=on) |
结构化蒸馏 | ✅ | ICML 2026 对齐,11x 压缩(TRINITY_DISTILL_COMPRESS=on) |
个性化 | ✅ | PAHF 双反馈(Meta ICLR 2026 对齐) |
跨模态 | ✅ | 图搜文/文搜图闭环 |
DSH 结构融合 | ✅ | 6 表自动同步(会话/事件/goal/todo/header/schedule),goal objective 100% |
记忆可迁移 | ✅ | memory_portability.py:标准 JSON/NDJSON + Mem0/Zep 导入 |
记忆市场 | ✅ | TrustExchange:挂单/订单簿/定价/声誉(11 端点)+ 冷启动模拟(scripts/market_sim.py) |
联邦 | ✅ | 多实例 export/import/diff 同步 + sync-agent(单向增量+轮询) |
短期记忆符号卸载 | ✅ | Mermaid 画布 + node_id 溯源(/offload/*,原文落盘 refs) |
Persona 白盒画像 | ✅ | 命题聚合 → persona.md(/persona/*,TRINITY_PERSONA 默认 off) |
召回可解释 | ✅ | /memory/search/explain 分数分解(keyword/vector/rerank/final) |
一致性校验 | ✅ | scripts/consistency_check.py + maintenance |
环境体检 | ✅ | scripts/env_doctor.py(8 项只读检查,退出码 0/1/2) |
记忆可迁移(V2 核心)
# 导出标准格式(记忆护城河入场券:可进可出)
python scripts/memory_portability.py export --out memories.json
python scripts/memory_portability.py export --out memories.ndjson --format ndjson
# 导入(幂等:content_hash 去重)
python scripts/memory_portability.py import --file memories.json
# 从 Mem0 / Zep 迁移
python scripts/memory_portability.py import-mem0 --file mem0_export.json --persona p1
python scripts/memory_portability.py import-zep --file zep_export.json --persona p1Benchmark(实测;官方 LongMemEval_S 已跑,2026-08-16)
Benchmark | Score | 口径 |
LongMemEval_S(官方 ICLR 2025,500 题) | session R@5 = 0.968 · turn R@5 = 0.922 · hit pos 1.3 | 官方数据集实测(hf-mirror 获取),hybrid top-5 |
SQuAD v1.1 (adapted) | R@5 = 98.3% | 180 题 passage selection(本地) |
LoCoMo (subset) | R@5 = 0.88 | 38 题会话聚合(中文本地集) |
pytest | 815 passed / 0 failed | 全量 |
LongMemEval_S 500 题 QA(judge3 三票,RouteReasoner 产品化策略路由 + pref-inner2) | 68.6%(343/500) | 2026-08-17 全量;SS-A 96.4 / SS-U 92.9 / KU 69.2 / TR 65.4 / SS-P 56.7 / MS 49.6 |
LongMemEval_S 500 题 QA(judge3 三票,route2 benchmark 脚本) | 63.2%(316/500) | 2026-08-17 基线;MS 43.6 / SS-P 20.0 |
LongMemEval_S 500 题 QA(dated,旧 judge) | 54.0% | 2026-08-16 全量实测 |
📊 官方 LongMemEval_S 详情与分题型:docs/bench-official/LongMemEval_S_REPORT_20260816.md QA accuracy(DeepSeek judged,官方模板,500 题)= 54.0%(dated 优化:时间戳+全量证据+ temporal 分步推理;优化前基线 49.6%,temporal-reasoning +15.7pp)。 分题型:assistant 91% / user 87% / knowledge-update 64% / multi 36% / temporal 44% / preference 3%。
⚠️ 口径声明(2026-08-16):README 旧版引用的 "LongMemEval 96.4% / BEAM 10M 64.1%" 系 Exabase M-1 / Hindsight 的成绩,非 Trinity 实测,已移除。BEAM/LoCoMo 英文官方集 仍未跑(网络限制),不构成对外宣称。
Research Foundation
Trinity 的 second_brain 与 2026 前沿对齐:PPR/HippoRAG 2、SimpleMem (ICML 2026)、
Structured Distillation (11x)、PAHF (Meta ICLR 2026)、Hindsight/BEAM、Mem0/Zep/Graphiti 思路。
Requirements
Python 3.11+(推荐 3.14)
Docker Desktop(容器化部署)
jieba(中文分词)、fastapi、strawberry-graphql
License
MIT — see pyproject.toml.
Trinity: model changes, framework changes, memory doesn't.
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Servers
- AlicenseNot gradedqualityCmaintenanceProvides persistent long-term memory for AI agents with semantic search and activation-based decay. Enables AI systems to remember across sessions through layered memory architecture and automatic context-aware retrieval.31MIT
- AlicenseAqualityBmaintenanceEnables AI agents to manage hierarchical memory with Markdown-based storage, tiered architecture (L0-L3), and hybrid retrieval for transparent and persistent context.8MIT
- AlicenseNot gradedqualityAmaintenancePersistent memory for AI agents with semantic memory, belief tracking, and dream consolidation, enabling cross-session knowledge retention.3149MIT
- AlicenseNot gradedqualityAmaintenanceA high-performance memory management system for AI agents with 200+ tools including 4-tier memory architecture, advanced RAG pipeline, and Git-like versioning.1MIT
Related MCP Connectors
Persistent memory and knowledge management for AI agents with semantic search and 50+ tools.
Persistent memory and knowledge graphs for AI agents. Hybrid search, context checkpoints, and more.
Sovereign Agent OS — Persistent Memory, Governance & Compliance for AI Agents.
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/trinity-tick/trinity'
If you have feedback or need assistance with the MCP directory API, please join our Discord server