Integrations¶

neuroflow connects to four MCP (Model Context Protocol) servers that Claude Code launches automatically via npx. One requires credentials; three work out of the box.

MCP servers¶

Server	npm package	Requires credentials
PubMed / bioRxiv	`paper-search-mcp-nodejs`	❌ None
Miro	`@k-jarzyna/mcp-miro`	✅ `MIRO_ACCESS_TOKEN`
Context7	`@upstash/context7-mcp`	❌ None

All are started automatically by Claude Code — you do not need to run them manually.

PubMed / bioRxiv¶

The paper-search-mcp-nodejs server handles both PubMed and bioRxiv searches — no credentials required.

The scholar agent uses it to search NCBI PubMed for peer-reviewed literature and bioRxiv for preprints.

bioRxiv¶

The bioRxiv integration enables the scholar agent to search preprints.

No credentials needed. Works automatically after installation.

Preprints are not peer-reviewed

The scholar agent marks all bioRxiv results with ⚠️ PREPRINT. Preprints have not been peer-reviewed and should be treated with appropriate caution.

bioRxiv API keyword-search limitation

The bioRxiv MCP server uses a date-range API that does not support keyword filtering. When a keyword search returns zero results, the scholar agent will warn you and automatically fall back to CrossRef and Semantic Scholar — both free public APIs that support full keyword search across preprints and peer-reviewed literature. No additional setup is required for the fallback.

Miro¶

The Miro integration enables Claude to create and edit Miro boards — useful for mind maps, experiment diagrams, and visual collaboration during ideation.

Getting a personal access token¶

Go to https://miro.com/app/settings/user-profile/apps
Click Create new app (or select an existing one)
Under Token, click Create token
Copy the token — it starts with eyJ…

No OAuth support

Miro OAuth browser login is not supported from a terminal subprocess. Use a personal access token instead.

Setup¶

Run the wizard:

/neuroflow:setup

Or set the environment variable directly:

export MIRO_ACCESS_TOKEN="eyJhbGciOiJSUzI1NiJ9..."

Context7¶

The Context7 integration provides Claude with up-to-date documentation for libraries like MNE, nilearn, scikit-learn, and PsychoPy — directly in context.

No credentials needed. Works automatically after installation.

This means when Claude writes an MNE preprocessing script, it can look up the current API instead of relying on training data that may be outdated.

Custom LLM providers¶

neuroflow's /setup command (Step 5) lets you configure an alternative LLM API endpoint for Claude Code — replacing Anthropic's API with any OpenAI-compatible endpoint.

e-INFRA CZ (Czech academic researchers only)¶

Access requirement: e-INFRA CZ LLM API is available to Czech academic researchers with Metacentrum/e-INFRA CZ membership. See https://metavo.metacentrum.cz for eligibility. This service is not available for general international use.

The e-INFRA CZ platform provides free access to large open-source models via an OpenAI-compatible API at https://llm.ai.e-infra.cz.

Available models:

Model	Category	Notes
`qwen3.5-122b`	General / best overall	Default recommended
`qwen3-coder-next`	Coding	Latest coding model
`deepseek-v3.2`	Coding + reasoning	Good all-rounder
`deepseek-v3.2-thinking`	Reasoning / thinking	For complex reasoning
`kimi-k2.5`	Agentic / tool use	Best for tool-calling workflows
`mistral-small-4`	Fast / small	Quick tasks
`qwen3-coder-30b`	Fast / coding	Lighter coding model

Direct connection:

ANTHROPIC_BASE_URL=https://llm.ai.e-infra.cz/v1 \
ANTHROPIC_API_KEY=<YOUR_API_KEY> \
claude

Proxy mode (for model selection):

Copy skills/setup/scripts/proxy.mjs from the neuroflow plugin, edit in your API key, then:

node proxy.mjs kimi-k2.5   # Terminal 1 — start the proxy
# Close Claude Code, then reopen in Terminal 2:
ANTHROPIC_BASE_URL=http://localhost:3456 ANTHROPIC_API_KEY=any claude

For full documentation — including all available models, direct mode limitations, and the complete terminal workflow — see the neuroflow:setup skill → references/einfra-cc.md.

Other providers¶

Any OpenAI-compatible endpoint works: set base_url and api_key during /setup Step 5. The custom LLM settings are saved to .neuroflow/integrations.json under the custom_llm key.

Credential storage¶

When you run /neuroflow:setup, credentials are saved to .neuroflow/integrations.json:

{
  "miro": {
    "MIRO_ACCESS_TOKEN": "eyJ..."
  },
  "custom_llm": {
    "provider": "einfra",
    "base_url": "https://llm.ai.e-infra.cz/v1",
    "api_key": "<stored locally, gitignored>",
    "model": "qwen3.5-122b"
  }
}

Never committed

.neuroflow/integrations.json is automatically added to .gitignore by neuroflow. Your credentials are stored locally only and never committed to your repository.

Reminder behavior¶

neuroflow checks credentials at the point of use, not upfront:

Trigger	Reminder
Mention Miro in any command	If `MIRO_ACCESS_TOKEN` missing → offer to run `/setup` or skip
Mention custom LLM / e-INFRA	If `custom_llm` missing → offer to run `/setup` Step 5

You can always re-run /neuroflow:setup to add or update credentials at any time.