01 / CAPABILITY
SE
Session-aware updates
Give each AI chat or task a readable session name, then associate its memory entries with that session.
Agent memory / Model Context Protocol (MCP) server
Hosted MCP memory for AI agents.
Shared context between chats.
Create Agent Memory in datamcp and get a hosted Model Context Protocol link for shared AI project context. Compatible chats can append structured updates, search earlier work, and prepare compact handoffs.
Free: 1 Agent Memory + 1 MCP linkRead Only or Read & AppendNo local memory server
SHARED MEMORY / LIVE3 AI CHATS / 1 HOSTED MCP LINK
AI CHATS
Claude search
Cursor append
Codex handoff
HOSTED MCPdatamcpauth · access · tools
SHARED PROJECT RECORDAgent Memorystructured · searchable · append-only
Claude
search_memory8 entries foundCursor
append_memoryprogress savedCodex
create_handoff_contexthandoff readyACCESSPer MCP link
MODERead / Append
STORAGEHosted
FORMATStructured
Direct answer
What does a hosted MCP memory server do?
A hosted MCP memory server gives compatible AI clients a shared, tool-accessible project record without requiring you to operate a local database, custom MCP runtime, or synchronization service.
- Best fit
- Projects where multiple AI chats or agents need to leave durable progress, decisions, blockers, deploy notes, and handoff context for one another.
- Available tools
- register_session, append_memory, search_memory, get_memory_entry, and create_handoff_context.
- Storage model
- Structured append-only entries with Markdown bodies, summaries, tags, files, entry types, importance, metadata, and session attribution.
- Search model
- PostgreSQL full-text search with filters. This release does not provide vector embeddings or semantic recall.
- Write control
- Read Only links block session registration and memory writes. Read & Append and Full Access links allow the current write tools.
- Not included
- No automatic task-completion writes, verified agent identity, direct .md upload, edit/delete tools, or replacement for Git and project documentation.
The production path
A shared project record that AI clients can use
AI chats often lose the decisions that matter between sessions. One chat changes an API contract, another investigates a production bug, and a third starts without knowing either happened. Copying entire transcripts is noisy and usually includes more context than the next task needs.
Agent Memory gives each compatible client a small set of explicit Model Context Protocol tools. A client registers a human-readable session name, appends meaningful updates, searches earlier entries, and requests a compact handoff when another chat needs to continue the work.
The current system is deliberately structured and append-only. It records what an agent chose to write, not every conversation automatically. Search uses PostgreSQL full-text search and filters rather than embeddings. That makes the behavior understandable, but it also means clients need clear instructions about when and what to save.
Read what agent memory is and when to use it, or follow the Agent Memory setup reference for tools, permissions, and limits.
What you get
Production access.
Without production guesswork.
02 / CAPABILITY
ST
Structured project memory
Store summaries, Markdown details, decisions, risks, deploys, tags, files, importance, and metadata in a consistent entry model.
03 / CAPABILITY
FI
Filtered full-text search
Search project history by text and narrow results by date, tags, files, type, importance, or session.
04 / CAPABILITY
CO
Compact handoff context
Create a bounded summary of recent or filtered entries instead of pasting full chat transcripts into the next agent.
05 / CAPABILITY
PE
Per-link write control
Use Read Only for retrieval or Read & Append when a trusted client should record new project context.
06 / CAPABILITY
HO
Hosted remote MCP
Connect through one HTTPS MCP endpoint without running a local memory server or maintaining its storage layer.
Source to controlled MCP link
One. Two.
Three.
Create the memory once. datamcp hosts its storage, remote MCP transport, client authentication, search tools, and per-link write boundary.
Read the setup guide- 01Create Agent Memory
Add an Agent Memory connection and give the shared project record a clear name and purpose.
- 02Choose link access
Create a Read Only or Read & Append MCP link depending on whether the client should only recall context or also record updates.
- 03Connect each AI client
Add the hosted MCP URL to compatible clients and instruct each chat to register its session and append meaningful handoff entries.
Build or use datamcp
Hosted Agent Memory vs. copying chat context
See what stays on your engineering backlog when the MCP runtime and control layer are managed for you.
CAPABILITYdatamcpManual notes and transcripts
Shared accessOne MCP memory for compatible clients
Copy and paste between chats
Context shapeStructured summaries and Markdown entries
Long transcripts or inconsistent notes
RecallFull-text search with filters
Manual document or chat search
HandoffsCompact context from selected entries
Rebuild context by hand
Write boundaryRead Only or Read & Append per link
Controlled by access to the whole document
Frequently asked questions
Questions before
you connect.
Clear answers about architecture, access, credentials, and supported clients.
What is an MCP memory server?
An MCP memory server exposes memory tools through the Model Context Protocol. AI clients can use those tools to register a session, append structured project updates, search previous entries, retrieve a full entry, and prepare handoff context.
What can an AI agent store in datamcp Agent Memory?
An entry can include a title, summary, Markdown body, entry type, importance, tags, file paths, metadata, session ID, and occurrence date. Entry types include notes, progress, decisions, bugs, handoffs, deploys, tasks, and risks.
Is this semantic or vector memory?
No. The current search uses PostgreSQL full-text search plus filters such as tags, files, entry type, importance, session, and date range. Do not treat it as embedding-based semantic recall.
Can agents edit or delete memory entries?
No. The current MCP workflow is append-only. Agents can append new entries, search them, retrieve one entry, and create handoff context, but update and delete tools are not available.
Does datamcp automatically write after every task?
No. The connected AI client must call append_memory as part of its own instructions or workflow. datamcp provides the tools and hosted storage, but it does not force a client to record an update.
Can I upload a Markdown file and turn it into an MCP server?
Not in the current release. Memory entry bodies support Markdown, but direct .md file import, synchronization, and export are not available.
How are memory writes controlled?
Use a Read Only MCP link to allow search and retrieval without writes. Use Read & Append or Full Access when a client should register sessions and append entries. Each MCP link can be revoked individually.
Does Agent Memory replace Git, documentation, or issue tracking?
No. It is a compact coordination layer for AI chats and agents. Keep source code in version control, durable documentation in its canonical system, and formal work items in the appropriate tracker.
Keep exploring
Related guides.
GUIDE
Claude persistent memory options
Compare Claude Memory, project memory, CLAUDE.md, Claude Code auto memory, and a shared MCP memory server.
GUIDEWhat is agent memory?
Understand persistent context, shared project memory, MCP tools, and the limits of the current approach.
GUIDEAgent Memory documentation
Create a memory connection, choose link access, and use the five available MCP tools.
GUIDEHosted MCP gateway
See how datamcp hosts remote MCP endpoints and controls client access across supported source types.
GUIDEMCP permissions and scopes
Separate client identity, MCP-link permissions, backend access, and revocation.
Start with one link
Create one shared memory for all your AI chats
Create Agent Memory in datamcp, receive a hosted HTTPS MCP link, and connect compatible AI clients to the same project record. The Free plan includes 1 connection and 1 MCP link, with no credit card required.