SimBrain
SimBrain writes local data incrementally to Elasticsearch and provides MCP tools and a CLI for data ingestion, project viewing, progress monitoring, and retrieval—a prerequisite for implementing RAG.
Install / Use
claude mcp add jyh20030112 -- npx -y github:jyh20030112/SimBrainIf the server publishes to npm under a different name, use that package instead — check the repo README.
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View source on GitHubSimBrain
简体中文 | English
SimBrain incrementally ingests local documents into Elasticsearch and provides MCP tools and CLIs for ingestion, project inspection, progress monitoring, and retrieval.
Quick start
SimBrain defaults to local Ollama at http://localhost:11434 with the bge-m3 model. Start Ollama and install the model first:
ollama pull bge-m3
Every usage mode requires Elasticsearch. At minimum, configure its endpoint and authentication:
ES_URL=https://your-es-host:9200
ES_API_KEY=your_es_api_key
See .env.example for all fields and defaults. When running from source, copy it to .env:
cp .env.example .env
MINERU_API_TOKEN is optional. When configured, MinerU is preferred for PDF parsing; otherwise SimBrain falls back to pypdf.
Supported document formats: PDF, DOCX, TXT, TEXT, Markdown, CSV, and XLSX.
Use with MCP
SimBrain exposes an MCP server over standard input/output (stdio). Once published on PyPI, start it with:
uvx --from simbrain simbrain-mcp
The server exposes these tools:
| Tool | Arguments | Purpose |
| --- | --- | --- |
| simbrain-ingest | input_dir, output_dir, project | Incremental ingestion |
| simbrain-status | output_dir | List all projects |
| simbrain-status-realtime | output_dir, project | Monitor ingestion progress |
| simbrain-search | question, project, top_k | Hybrid vector and keyword retrieval |
Codex configuration
Add this to ~/.codex/config.toml:
[mcp_servers.simbrain]
command = "uvx"
args = ["--from", "simbrain", "simbrain-mcp"]
[mcp_servers.simbrain.env]
ES_URL = "https://your-es-host:9200"
ES_API_KEY = "your_es_api_key"
MINERU_API_TOKEN = "your_mineru_token"
Or register it from the command line:
codex mcp add simbrain \
--env ES_URL=https://your-es-host:9200 \
--env ES_API_KEY=your_es_api_key \
--env MINERU_API_TOKEN=your_mineru_token \
-- uvx --from simbrain simbrain-mcp
Claude Desktop configuration
Add this entry under mcpServers in claude_desktop_config.json:
{
"simbrain": {
"command": "uvx",
"args": ["--from", "simbrain", "simbrain-mcp"],
"env": {
"ES_URL": "https://your-es-host:9200",
"ES_API_KEY": "your_es_api_key",
"MINERU_API_TOKEN": "your_mineru_token"
}
}
}
Remove MINERU_API_TOKEN if MinerU is not needed. All remaining settings use the defaults from .env.example. To use an OpenAI-compatible embedding service, set EMBEDDING_PROVIDER, EMBEDDING_URL, EMBEDDING_API_KEY, and EMBEDDING_MODEL together.
Use with the CLI
The examples below use the PyPI package. When developing this repository, replace uvx --from simbrain with uv run.
Incremental ingestion
uvx --from simbrain simbrain-ingest \
--input-dir ./docs \
--output-dir ./output \
--project my-knowledge-base
Files with the same name are updated, unchanged files are skipped, and historical files omitted from the current input are retained.
List all projects
uvx --from simbrain simbrain-status --output-dir ./output
Monitor ingestion progress
uvx --from simbrain simbrain-status \
--output-dir ./output \
--project my-knowledge-base
Search a project
uvx --from simbrain simbrain-search \
--question "How do I configure access permissions?" \
--project my-knowledge-base \
--top-k 10
top-k must be between 1 and 100. Results contain source chunks and metadata; SimBrain does not generate an LLM answer.
Output and tests
Successful CLI calls return JSON. The progress command emits JSON Lines when its state changes.
Run tests:
uv run pytest -q
To include the Elasticsearch integration test:
SIMBRAIN_TEST_ES_URL=http://localhost:9200 uv run pytest -q -m integration
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