Ermöglicht semantische Suche über eine lokale Wissensdatenbank, damit KI-Clients relevante Textstellen finden können, ohne das Context Window zu belasten.
Auch bekannt als VBlackJack/Cortex, cortex-local-rag
- Stars
- 1
- Tools
- 4
- Downloads, 30 Tage
- 2.443
- Neueste Version
- 2026.1021.3
- Letzter Commit
- 21. Okt. 2026
- Lizenz
- Apache-2.0
Was ist Cortex MCP?
Cortex ist ein MCP server. Ermöglicht semantische Suche über eine lokale Wissensdatenbank, damit KI-Clients relevante Textstellen finden können, ohne das Context Window zu belasten. Er stellt 4 Tools bereit, etwa cortex_search, cortex_sync, cortex_list_sections.
Zusammenfassung generiert aus dem README des Projekts
Über Cortex MCP server
Cortex bietet semantische Suchfunktionen für eine lokale Wissensdatenbank. So können KI-Clients wie Claude, Gemini und Cursor relevante Textpassagen abrufen, ohne das Context Window zu erschöpfen. Es fungiert als MCP server, der Dokumente lokal verarbeitet und indiziert, sodass deine Inhalte auf deinem Rechner bleiben. Das System unterstützt Englisch und Französisch durch multilingualen Vektor-Retrieval unter Verwendung des paraphrase-multilingual-MiniLM-L12-v2 Modells.
Nutzer können ihre Daten über das Cortex Companion Interface oder über ein CLI verwalten. Der Server unterstützt verschiedene Dokumentenformate wie Markdown und PDF und bietet einen optionalen Confluence-Writer, um freigegebene Spaces zu importieren. Entwickler können wählen, ob sie einen gesamten Ordner oder spezifische benannte Sektionen indizieren möchten. Das Setup ist über einen einheitlichen Windows-Installer verfügbar, der kein separates Python oder .NET Runtime benötigt, oder als Standalone-Archive für macOS und Linux.
Was du damit machen kannst
- 1Semantische DokumentensucheLass einen KI-Client mithilfe von bedeutungsorientierter Suche gezielte Informationen in deinen lokalen PDF- oder Markdown-Dateien finden.
- 2Confluence-WissensintegrationSynchronisiere spezifische Confluence Spaces in deine lokale Wissensdatenbank für KI-gestützte Abfragen.
- 3Organisierte Suche nach SektionenBegrenze den Suchbereich der KI auf bestimmte Unterordner wie Projekte oder Notizen, um die Relevanz zu erhöhen.
Geschrieben aus dem README des Projekts. Jeder Use Case wurde gegen ein Zitat daraus geprüft.
So installierst du Cortex MCP
Formate geprüft am 10. Nov. 2026Cortex MCP in Claude Code installieren
$ claude mcp add --env CORTEX_KB_PATH=<CORTEX_KB_PATH> cortex -- uvx cortex-local-ragCortex MCP in Cursor installieren
~/.cursor/mcp.json
{
"mcpServers": {
"cortex": {
"command": "uvx",
"args": [
"cortex-local-rag"
],
"env": {
"CORTEX_KB_PATH": "<CORTEX_KB_PATH>"
}
}
}
}Cortex MCP in VS Code installieren
.vscode/mcp.json
{
"servers": {
"cortex": {
"type": "stdio",
"command": "uvx",
"args": [
"cortex-local-rag"
],
"env": {
"CORTEX_KB_PATH": "<CORTEX_KB_PATH>"
}
}
}
}Cortex MCP in Claude Desktop installieren
claude_desktop_config.json
{
"mcpServers": {
"cortex": {
"command": "uvx",
"args": [
"cortex-local-rag"
],
"env": {
"CORTEX_KB_PATH": "<CORTEX_KB_PATH>"
}
}
}
}Cortex MCP in Codex installieren
~/.codex/config.toml
[mcp_servers.cortex] command = "uvx" args = ["cortex-local-rag"] [mcp_servers.cortex.env] CORTEX_KB_PATH = "<CORTEX_KB_PATH>"
Cortex MCP in Gemini CLI installieren
~/.gemini/settings.json
{
"mcpServers": {
"cortex": {
"command": "uvx",
"args": [
"cortex-local-rag"
],
"env": {
"CORTEX_KB_PATH": "<CORTEX_KB_PATH>"
}
}
}
}Cortex MCP tools 4
Erkannt aus dem READMEcortex_searchcortex_synccortex_list_sectionscortex_freshness
| cortex_search | — | |
| cortex_sync | — | |
| cortex_list_sections | — | |
| cortex_freshness | — |
Konfiguration
CORTEX_KB_PATHErforderlichAbsolute path to the local knowledge base Cortex indexes and serves.
| Name | Beschreibung | Typ |
|---|---|---|
| CORTEX_KB_PATH | Absolute path to the local knowledge base Cortex indexes and serves. | Erforderlich |
Automatisierte Checks
Geluften am 12. Nov. 2026Vollständiger Bericht →Unsere automatisierten Checks bestanden. Das ist kein Security-Audit: Lies den Code und gib dem Server nur den minimal notwendigen Zugriff. Wie die Checks funktionieren
- Source Repository verknüpft und erreichbarBestanden
- Open Source Lizenz (OSI)Bestanden
- Commit oder Release im letzten JahrBestanden
- Package-Name ähnelt keinem populären PackageBestanden
- Remote Endpoint nutzt HTTPSNicht geprüft
- Destruktive Tools sind markiertBestanden
- Keine versteckten Anweisungen an das ModellBestanden
- Kein kritischer Hinweis im Paket oder seinen AbhängigkeitenBestanden
README
Auf GitHub ansehenCortex - RAG MCP for a knowledge base
English | Français
Cortex is an MCP (Model Context Protocol) server that exposes semantic search over a local knowledge base. It lets Claude, Codex and Gemini find the right passage in your documents without wasting their context window. Search is semantic (by meaning, not keyword), in French and in English. Cortex processes and indexes the knowledge base locally without sending its content; the MCP client may still pass requested chunks to its model under its own policy. The optional Confluence writer only downloads explicitly allowlisted spaces; the generated Markdown, vector index, and lexical index remain local.
Starting with 2026.0906.01, Companion offers a guided home screen, operation history and Confluence setup from one page or space link. Connection and measured scope confirmation stay in the flow; successful collection is followed by indexing. Use the combined installer to keep Cortex and Companion compatible.
Since 2026.0909.02, Confluence updates preserve the served generation when subtree enumeration fails and apply changed target/classification settings on retry. Search uses multilingual vector retrieval by default; CLI and MCP callers can explicitly select hybrid or reranked search. The first successful collection after upgrading regenerates older publication revisions, and the following sync removes obsolete index entries.
Guided document updates (2026.0909.00)
Companion brings local documents and Confluence together in My sources, with one Update my documents action. Search previews are resizable, large page trees render visible rows, and cancelling review preparation keeps the draft. Readiness now follows the saved document folder and configuration, including after restart. Run one document update after upgrading to establish this evidence for older indexes. See the release notes.
Measured scope without enumerating the space (2026.0907.00)
Adding a Confluence source measures its page, subtree and whole-space scopes with one indexed count each instead of reading the space page by page. On a 5916-page space that measurement took 3 min 19 s, past the timeout of every graphical caller, so Companion showed nothing at all. It now answers in about a second, and the emitted contract is unchanged.
Two whole-space numbers shift by one as a result: the resolved page is no longer folded into the space total, and a space with no visible page reports zero rather than one. A deployment whose search endpoint returns no total cannot measure a scope and reports that as a permanent failure instead of a retryable one. See the contracts.
Paired Companion 2026.0907.00 restores the contrast of the scope window, whose options were drawn in the system text colour, and stops reporting a timeout as a connection failure or advising a delay increase that silently reverts.
Source management in Companion (2026.0906.02)
The workflow includes search, remote page trees, impact review, evidence-based readiness, save-and-update, last-removal undo and recovery actions. See the contracts.
Paired version 2026.0906.02 provides visible My sources cards, a prefilled selection editor, confirmed page/space removal and browser links to originals. Removal only changes Cortex tracking; search reflects it after successful collection and indexing.
Removing the final source explicitly writes spaces = [] in a schema v2 or v3
configuration. This intentional empty allowlist permits an empty publication
with tombstones for prior documents. An absent spaces key remains incomplete
configuration and collection is refused. Connection and credential validation
and publication safeguards still apply. Both updated components are required;
this capability is absent from the installed 2026.0906.01 release.
Installation
Windows, no Python (recommended)
The simplest path: one installer for Cortex, Cortex Companion, the windowless Confluence converter, and the offline models. No separate Python or .NET runtime is required.
- Download
Cortex-Setup.exeandSHA256SUMSfrom the latest release. - Before running the unsigned installer, calculate its digest with
Get-FileHash .\Cortex-Setup.exe -Algorithm SHA256in PowerShell and verify that it exactly matches theCortex-Setup.exeline inSHA256SUMS. - Double-click only after that check. If SmartScreen still warns, select
More info, thenRun anyway. - Choose the folder that holds your documents, keep
Index everything in this folder, and finish. Cortex Companion opens when installation completes. Indexing only starts when you request synchronization in Companion. - In Companion, open
Settingsand verify the knowledge-base folder. The Cortex executable installed with Companion is detected automatically. - Drop your documents in that folder, open
Local database, then selectSynchronize local documents. - Restart your AI application: Cortex shows up there as an MCP server.
Companion then lets you synchronize, schedule, diagnose, and configure Cortex without a terminal. Details, silent mode and reinstall: Windows install.
Standalone archives (Windows x64, macOS Apple Silicon, Linux x64)
Every release also ships one ZIP archive per platform. It unpacks to a cortex/
folder holding the cortex or cortex.exe executable (MCP server + CLI, no
Python), its runtime, and the licenses for every embedded dependency; keep the
folder whole. See Standalone distribution.
From PyPI (Python, advanced)
py -m pip install --upgrade cortex-local-rag
cortex setup
This path installs the CLI and MCP server, but not Cortex Companion. The model is downloaded on first use if its cache is empty.
From source (development)
:: From the folder where you cloned Cortex
install.bat
install.bat and sync.bat are the development path for a source checkout,
not a supported end-user installation: install.bat installs the unlocked
dependencies from requirements.txt, and sync.bat indexes the folder section
by section without the Confluence documents. To use Cortex, install
Cortex-Setup.exe or a standalone archive instead. Details:
Setup.
How it works
Documents folder (.md, .pdf) Optional Confluence writer (REST)
| |
| current Markdown generation
+------------------+-------------------+
|
v
cortex sync <- Split, hash, vectorize, update FTS5
|
v
%LOCALAPPDATA%\Cortex\ <- ChromaDB + lexical.db
|
v
cortex serve <- MCP server (FastMCP)
|
v
MCP clients <- Claude / Codex / Gemini / Antigravity / LM Studio / Cursor / Windsurf / VS Code
The embedding model is the multilingual ONNX
paraphrase-multilingual-MiniLM-L12-v2. The Windows installer bundles it; a
source installation or standalone binary downloads it when the local cache is
empty.
Two indexing modes
- Whole folder (default): anything you place in the chosen folder, at the root or in any subfolder, becomes searchable. Nothing to configure.
- Sections (advanced): limits indexing to named subfolders you can search
separately (defaults
knowledge,projects,notes).
These modes govern the user-selected document folder. Generated ingestion
documents are indexed separately from the current published generation with
source_kind=doc and section sources.
Details: Configuration.
The cortex command
The installed package exposes a single command:
| Subcommand | Purpose |
|---|---|
cortex setup |
Config + index + client registration in one go (--kb-path, --yes, --no-index, --reset). |
cortex serve |
Runs the MCP server (used by clients). |
cortex sync |
Incremental index synchronization. |
cortex search |
Searches the index from the console (debugging aid). |
cortex ingestion |
Shows source health and whether catch-up is due. |
cortex confluence |
Stores the PAT interactively or runs the allowlisted writer. |
cortex config |
Reads or changes configuration through an atomic JSON contract, notably for Companion. |
cortex daemon |
Runs, inspects or stops the shared per-user server used when [server] mode = "shared" (opt-in). |
cortex bundle |
Describes or verifies an encrypted portable archive. |
cortex doctor |
Installation diagnostics (read-only). |
cortex register / cortex unregister |
Adds or removes Cortex from MCP clients. |
cortex init |
Creates the single per-user configuration. |
cortex check |
Verifies the installation. |
cortex --help describes every subcommand and cortex <command> --help describes
its options. A prompt-free installation scripts as:
cortex setup --yes --kb-path "D:\Documents\Knowledge"
Exposed MCP tools
| Tool | Description |
|---|---|
cortex_search |
Multilingual vector search by default; optional retrieval_mode (vector, hybrid, rerank). Parameters: query, section, top_k (1-10), source/author filters, and occurred/updated date ranges. |
cortex_sync |
Triggers an incremental sync of the selected folder and, on a full sync, the current published document generation. |
cortex_list_sections |
Lists included sections and "out of policy" folders. |
cortex_freshness |
Read-only vault and ingestion freshness summary. Parameters: section (optional), include_entries (false by default). |
Documentation
- Table of contents
- Windows install: unified Cortex + Companion + Confluence converter + models installer, corpus choice, silent mode, reinstall.
- Standalone distribution: per-platform archives and reproducible builds.
- Install from source: prerequisites, MCP clients.
- User guide: sync, search, tools, doctor, logs.
- FAQ: installation, local data, sync, and diagnostics.
- Release notes: user-visible changes by version and the published-history notice.
- Technical changelog: complete changes by version.
- Configuration:
config.toml, indexing modes, sections, data home, migration. - Ingestion scheduling: source health, catch-up, retries, and Task Scheduler.
- Metadata v2 migration: structured search metadata, backup, migration, and restore.
- Confluence writer: allowlisted REST ingestion, Windows Credential Manager, conversion, and atomic generations.
- Reproducible install:
requirements.lock,--require-hashes, regenerating the lock. - Public specification: MCP surface, index contracts, data, distribution, and limits.
- Architecture: end-to-end and technical choices.
- Security: local runtime, telemetry off, single-writer.
Prerequisites
| Path | Requirements |
|---|---|
| Windows installer | No separate Python or .NET runtime. At least ~500 MB of space (applications, model + index). |
| Standalone archive | No Python. ~500 MB of space (model + index). |
| From source | Python 3.11 to 3.13. ~500 MB of space. |
| Client | Claude Desktop/Code, Codex, Gemini, Antigravity, LM Studio, Cursor, Windsurf or VS Code (MCP support). |
License
Apache 2.0. See LICENSE.
Retrieval validation
See the validation guide for the desktop JSON search contract, the isolated FR/EN relevance corpus, performance measurements and exact paired-commit checks.
Cortex MCP Fragen
Wie füge ich Cortex MCP zu Claude Code hinzu?
Führe claude mcp add --env CORTEX_KB_PATH=<CORTEX_KB_PATH> cortex -- uvx cortex-local-rag in deinem Terminal aus. Füge --scope user hinzu, damit der Server in jedem Projekt verfügbar ist.
Wie füge ich Cortex MCP zu Cursor hinzu?
Öffne ~/.cursor/mcp.json und füge den Server unter mcpServers hinzu, mit der Cursor-Config aus dem Installationsabschnitt oben.
Welche Tools bietet Cortex MCP?
Er stellt 4 Tools bereit, darunter cortex_search, cortex_sync, cortex_list_sections, cortex_freshness.
Sendet Cortex meinen Dokumenteninhalt in die Cloud?
Nein, Cortex verarbeitet und indiziert die Wissensdatenbank lokal, ohne den Inhalt zu versenden.
Welche Sprachen unterstützt die semantische Suche?
Die Suche ist multilingual und unterstützt sowohl Französisch als auch Englisch.
Kann ich Cortex mit Confluence nutzen?
Ja, es gibt einen optionalen Confluence-Writer, der explizit auf einer Allowlist stehende Spaces herunterlädt.