
KIAgent
com.localkiagentPublished by localkiagent.comOfficial publisherv0.53.0Updated Oct 24, 2026
Your mail, chats and documents indexed into a local SQLite corpus, served to AI clients over MCP.
Overview
KIAgent is a desktop app that indexes your mail, documents and chats into a local SQLite corpus and serves it to AI assistants over MCP.
- What you can do
- Query a locally indexed personal corpus of mail, documents, chats and notes through MCP tools exposed by the app's HTTP server or a stdio entry point for desktop clients. Ingestion runs on your machine: sources such as Gmail, IMAP, Microsoft 365 and local folders are pulled on a cadence and converted into indexed documents. Parsing, OCR and vision for scanned documents and images run locally with on-device inference via llama.cpp. A plugin and marketplace system adds further connectors, each permission-gated and isolated from the host capabilities.
- When to use it
- Use it when you want an AI assistant to answer with context from your own mail, files and notes while that data stays on your computer, and when you prefer a self-hosted, open-source knowledge layer over a cloud service.
- Requirements
- The KIAgent desktop app running on your machine, which hosts the MCP server; the manifest lists a remote endpoint at a per-user subdomain. Source connectors need their own accounts and OAuth client credentials, which OAuth-backed sources read from the environment at build time. Local model and vision helpers are fetched by a vendoring script.
Installation
In SourceWeft
- Open KIAgent in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.
Other MCP clients
Follow the launch instructions in the repository.
README
KIAgent
Your personal AI brain — local, open source, speaks MCP.
Website · Download · Architecture docs
[KIAgent main window — Sources screen with Gmail and HubSpot syncing]
Everyone is building the company a brain — a knowledge layer that ingests everything an organization knows, so AI can answer and act with real context. KIAgent is that layer for you personally. A company brain lives in someone else's cloud and belongs to your employer; your personal AI brain runs on your own machine, works with whatever AI you choose, and is yours forever.
Concretely, KIAgent is a desktop app that ingests your personal data — mail, documents, chats, notes — on your own machine, stores it in a local database, and serves it to AI assistants over MCP. Everything stays on your computer: ingestion, parsing, OCR and vision all run locally — with on-device inference powered by llama.cpp — so your AI assistant can know your world without your data ever leaving your machine.
At its core, KIAgent is a platform: a small set of host capabilities (MCP, database, local LLM, filesystem, web access) wired together by an ingestion engine, plus a plugin/extension system that lets sandboxed connectors use those capabilities to bring in new data sources.
Plugins sit at the center: each one connects to a third-party service (Gmail, Drive, Slack, Notion, ...) or the local filesystem, pulls your data in, uses the local LLM to process it, and lands it in the database — which MCP then serves to AI assistants. Access is mediated and permission-gated; plugins never touch these capabilities directly.
This repo: kiagent-core
This repository is the MIT-licensed core that KIAgent is built from, in the same spirit as VS Code and Code-OSS:
- kiagent-core (this repo) — the open-source core.
npm run package:ossproduces an unbrandedkiagent-corebuild you can run and redistribute under the MIT license. - KIAgent — the branded, signed product built from this core and distributed at localkiagent.com/download.
OAuth-backed sources (Gmail, Microsoft) read client credentials from the environment at build time — see .env.example / CI secrets. Forks and OSS builds supply their own OAuth client IDs.
Main components
- Ingestion engine (
src/main/core/engine) — pulls batches from sources on a cadence, converts raw items (mail, PDFs, images) into indexed documents, and commits them to the store. Built-in sources live insrc/main/sources(Gmail, IMAP, Microsoft 365, local folders). - Database (
src/main/core/store,src/main/db) — a SQLite corpus (better-sqlite3) holding documents, metadata and search indexes, written by the app and read by the MCP processes. - MCP server (
src/main/core/mcp,src/main/mcp) — exposes the corpus to AI assistants over two transports sharing one tool registry: an HTTP server inside the app, and a standalone stdio entry point that clients like Claude Desktop spawn directly. - Local LLM (
src/main/providers/local-llm,src/main/providers/apple-vision) — on-device inference via a bundled llama.cpp server (backend auto-detection, curated model tiers) plus native OCR/vision helpers for scanned documents and images. - Filesystem — local-folder ingestion, model storage, temp workspaces for conversion workers (
src/main/workers,src/main/converter). - Web — outbound HTTP for source APIs, OAuth flows (
src/main/auth,src/main/platform/oauth-providers.ts), and marketplace downloads. - Plugin / extension system (
src/main/platform,src/main/marketplace) — connectors run in isolated host processes with a manifest-declared, permission-gated view of the platform (sources, auth, storage, network). A GitHub-backed marketplace handles discovery, install and updates. A second, privileged tier lets a product build ship first-party extensions inside the app package itself — seedocs/architecture/extension-platform.mdfor the full model, including the bundled/unsafe.mainProcesstier andproduct.json. - Renderer (
src/renderer) — the React UI: source setup, marketplace, MCP connection status, settings and logs.
Developing
Other useful scripts:
Repository layout
MCP directories
KIAgent is published on the official MCP registry as com.localkiagent/kiagent (see server.json) and listed on Glama:
Acknowledgements
KIAgent's on-device inference is powered by llama.cpp, created by Georgi Gerganov and maintained by the ggml-org community (MIT license). The app bundles prebuilt llama-server binaries from the official llama.cpp releases (npm run vendor:inference fetches them at build time). Running capable models privately on consumer hardware is only practical because of their work — thank you.
License
MIT — see LICENSE.
Source: README.md at commit b3ebcb6
Tools
0Version history
1- v0.53.0LatestSep 16, 2026
Score
50% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
- Reached in the last 30 daysRequired25 pts
Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.
- Auth declaredRequired10 pts
Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.
- Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts