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MCP Server for Zep Cloud

MCP Server for Zep Cloud

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github.com/kev-huMemory & Knowledge11Updated 27w ago

About MCP Server for Zep Cloud

MCP Server for Zep Cloud connects AI agent applications to Zep Cloud memory and graph capabilities. It provides tools for managing conversation context, graph data, and project resources.

Key features

  1. 01Add messages to conversation threads
  2. 02Retrieve assembled user context
  3. 03Add and search knowledge graph data
  4. 04Manage users, threads, and graphs
  5. 05Inspect graph structure and data
  6. 06Configure context templates

Use cases

  1. 01Store conversation messages for later context
  2. 02Search graph facts, entities, and episodes
  3. 03Inspect relationships across ingested content
  4. 04Manage Zep users, graphs, and context templates

MCP support

The MCP server exposes Zep Cloud memory and administrative operations as tools. Tool groups can be selected with ZEP_TOOLSETS.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"zep-cloud": {
"command": "npx",
"args": [
"-y",
"mcp-server-zep-cloud"
],
"env": {
"ZEP_CLOUD_API_KEY": "<ZEP_CLOUD_API_KEY>"
}
}
}
}
Run commandnpx -y mcp-server-zep-cloud
Environment variables to set
ZEP_CLOUD_API_KEYSecret

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npmmcp-server-zep-cloud

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

zep-mcp

MCP server for the Zep Cloud API — a context engineering platform for AI agent memory. Built with FastMCP and the zep-cloud Python SDK.

📖 The story

I originally built this project back in early 2025 when I was just learning how to code. It worked! ...technically. The old version had a fallback client that returned fake success responses when the API was down 😅, wrapper scripts for every platform imaginable, and enough redundant code to make future-me cringe.

A year later, I've learned a thing or two. So I burned it all down and rewrote it.

  • Before: 2 tangled client layers, 8 tools, fallback mode that lied to you, ~4,000 lines 💀
  • After: 1 clean server entry point, 13 tools covering the full Zep Cloud API, ~770 lines

Keeping the old git history because it's kinda funny lmao

Use cases

I use this for my own content — ingesting video scripts and viewer comments into Zep's knowledge graph to understand what I've covered, what my audience cares about, and what I should make next.

Map your content knowledge graph — ingest your scripts and audience comments. Zep auto-extracts topics, entities (e.g. people, groups, ideas), and the relationships between them across everything you've published.

Full knowledge graph built from content scripts and viewer comments

See what topics cluster together — explore how a specific entity connects to content pieces and topics. Blue nodes are your actual content; the surrounding topics show what themes appear across those videos and what commenters associate with that entity.

Entity relationship view showing startup connected to content and related topics from comments

Find content gaps — query for entities with many topic and entity connections but no linked content nodes. Those are things your audience is already thinking and talking about that you haven't made a video on yet.

Rich Asians entity with many topic connections but no content nodes — a content gap

Setup

python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

Copy .env.example to .env and fill in your Zep Cloud API key:

cp .env.example .env

Install the pre-commit hook to prevent accidentally committing secrets:

cp scripts/pre-commit .git/hooks/pre-commit

Run the server

source venv/bin/activate
python server.py

Or with FastMCP dev mode:

fastmcp dev server.py

Configuration

VariableRequiredDescription
ZEP_API_KEYYesZep Cloud API key
ZEP_TOOLSETSNoComma-separated tool groups to enable. Values: memory, admin. Defaults to memory,admin (all tools).

Tools

13 tools organized by jobs-to-be-done:

Memory tools (memory):

  • add_messages — Add messages to a conversation thread
  • get_context — Get assembled context block for a user
  • add_graph_data — Add data to a knowledge graph (text, JSON, message, or triple)
  • search_graph — Search a knowledge graph for facts, entities, or episodes
  • get_task — Poll status of an async Zep operation

Admin tools (admin):

  • manage_user — User CRUD (create, get, update, delete, list, warm)
  • manage_user_instructions — Manage user summary instructions
  • manage_thread — Thread CRUD (create, get, delete, list)
  • manage_graph — Graph lifecycle (create, get, update, delete, list, clone)
  • manage_graph_structure — Graph schema, ontology, and custom instructions
  • manage_graph_data — Node, edge, and episode inspection and management
  • manage_context_templates — Context template CRUD
  • project_info — Get current Zep Cloud project info

Running tests

source venv/bin/activate
python -m pytest tests/

License

MIT

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.