Analyze customer feedback by stripping PII before processing to find stable themes and provide cited evidence for AI agents.
Also known as obsei/obsei
- Stars
- 1,452
- Tools
- —
- Downloads, 30 days
- —
- Latest version
- 1.1.1
- Last commit
- Nov 11, 2026
- License
- Apache-2.0
What is obsei MCP?
obsei is an MCP server. Analyze customer feedback by stripping PII before processing to find stable themes and provide cited evidence for AI agents.
Summary generated from the project's README
About obsei MCP server
obsei provides a self-hosted, open source solution for analyzing customer feedback while maintaining privacy. It functions by redacting personally identifiable information before data reaches a large language model, allowing users to identify stable themes across various channels and languages. This tool is designed for developers and teams who need to process feedback from sources like Slack or the App Store without compromising sensitive user details.
Users can deploy this via Python 3.11 or newer using uvx or pip. The system requires a database key and a pseudonym salt, which can be managed through a .obsei/secrets.env file or environment variables like OBSEI_DB_KEY and OBSEI_PSEUDONYM_SALT. It supports various optional modules including local classifiers, multilingual embeddings, and name redaction. You can integrate it into AI environments like Claude Code, Gemini, or any MCP client using the obsei mcp command.
What you can do with it
- 1Redact sensitive user informationAn AI agent can process customer messages while ensuring all personal data is stripped before storage.
- 2Identify recurring customer themesA developer can use the system to find consistent patterns and topics within large sets of feedback.
- 3Query feedback with source citationsYou can ask an AI agent questions about customer sentiment and receive answers backed by specific evidence.
- 4Connect multiple feedback channelsThe tool allows for the easy addition of different data sources like Slack or App Store reviews.
Written from the project's README. Every use case is checked against a quote from it.
How to install obsei MCP
Formats verified 10 Nov 2026Install obsei MCP in Claude Code
$ claude mcp add --env OBSEI_DB_KEY=<YOUR_OBSEI_DB_KEY> obsei -- uvx obseiInstall obsei MCP in Cursor
~/.cursor/mcp.json
{
"mcpServers": {
"obsei": {
"command": "uvx",
"args": [
"obsei"
],
"env": {
"OBSEI_DB_KEY": "<YOUR_OBSEI_DB_KEY>"
}
}
}
}Install obsei MCP in VS Code
.vscode/mcp.json
{
"servers": {
"obsei": {
"type": "stdio",
"command": "uvx",
"args": [
"obsei"
],
"env": {
"OBSEI_DB_KEY": "<YOUR_OBSEI_DB_KEY>"
}
}
}
}Install obsei MCP in Claude Desktop
claude_desktop_config.json
{
"mcpServers": {
"obsei": {
"command": "uvx",
"args": [
"obsei"
],
"env": {
"OBSEI_DB_KEY": "<YOUR_OBSEI_DB_KEY>"
}
}
}
}Install obsei MCP in Codex
~/.codex/config.toml
[mcp_servers.obsei] command = "uvx" args = ["obsei"] [mcp_servers.obsei.env] OBSEI_DB_KEY = "<YOUR_OBSEI_DB_KEY>"
Install obsei MCP in Gemini CLI
~/.gemini/settings.json
{
"mcpServers": {
"obsei": {
"command": "uvx",
"args": [
"obsei"
],
"env": {
"OBSEI_DB_KEY": "<YOUR_OBSEI_DB_KEY>"
}
}
}
}Configuration
OBSEI_DB_KEYSecretThe key that encrypts the database.
OBSEI_CONFIGPath to obsei.yaml (default ./obsei.yaml).
OBSEI_DBPath to the database, overriding store.path.
| Name | Description | |
|---|---|---|
| OBSEI_DB_KEY | The key that encrypts the database. | Secret |
| OBSEI_CONFIG | Path to obsei.yaml (default ./obsei.yaml). | |
| OBSEI_DB | Path to the database, overriding store.path. |
Automated checks
Ran Nov 12, 2026Full report →Passed our automated checks. That is not a security audit: read the code and give the server the narrowest access it needs. How checks work
- Source repository linked and reachablePass
- Open source license (OSI)Pass
- Commit or release in the last yearPass
- Package name not close to a popular packagePass
- Remote endpoint uses HTTPSNot checked
- Destructive tools are labelledNot checked
- No hidden instructions to the modelPass
- No critical advisory in the package or its dependenciesPass
README
View on GitHubobsei
Know what customers are saying. Keep what they said private. The self-hosted, open source alternative to Enterpret and Unwrap that strips PII before any LLM sees it. Collect feedback from every channel and language, redact personal data before it is stored, find stable themes, and let your AI agents answer questions with cited evidence.
Requires Python 3.11 or newer; on older Pythons, pip quietly installs the legacy 0.0.x, so keep the
>=1.0floor. 1.0 is not compatible with 0.0.x; for the legacy toolkit,pip install "obsei<1".
uvx --from "obsei[recommended]>=1.0" obsei init # or: pip install "obsei[recommended]>=1.0"
obsei try # redacted, labelled preview; nothing stored
obsei add appstore # add sources and sinks without editing YAML
obsei add slack
obsei check
obsei run
obsei init writes the database key and pseudonym salt to .obsei/secrets.env (owner-only,
git-ignored), which every command loads; on servers and in CI, set OBSEI_DB_KEY and
OBSEI_PSEUDONYM_SALT or mount the file.
Optional extras: recommended (local and embeddings), local (in-process classifier), sql, google, apple, names (person-name
redaction), embeddings (multilingual themes), notify (Telegram, Discord, email and more via Apprise).
Use it from your AI tool: /plugin install obsei --marketplace obsei/obsei in Claude Code,
gemini extensions install https://github.com/obsei/obsei, or uvx --from "obsei>=1.0" obsei mcp
in any MCP client. Codex, Copilot, VS Code, Cursor and others: https://docs.obsei.com/guides/ai-tools/
- Docs: https://docs.obsei.com
- Live demo: https://docs.obsei.com/demo/
- Source: https://github.com/obsei/obsei
- Container:
ghcr.io/obsei/obsei:1.1.1
obsei MCP questions
How do I add obsei MCP to Claude Code?
Run claude mcp add --env OBSEI_DB_KEY=<YOUR_OBSEI_DB_KEY> obsei -- uvx obsei in your terminal. Add --scope user to make it available in every project.
How do I add obsei MCP to Cursor?
Open ~/.cursor/mcp.json and add the server under mcpServers, using the Cursor config shown in the install section above.
How does obsei handle privacy?
It is a self-hosted alternative that strips PII (Personally Identifiable Information) before any LLM sees the data.
What are the Python version requirements?
The server requires Python 3.11 or newer to avoid installing legacy versions.
How can I use obsei with my AI tools?
You can install it via Claude Code, Gemini extensions, or use the MCP command in any MCP client.