Configuration

Configuration in Mimir is done through environment variables in a .env file. This guide organizes them by required and optional settings.

Configuration Overview

Mimir uses environment variables organized into these categories:

1. Server Configuration - API keys and server settings
2. Supabase Configuration - Database connection and settings
3. GitHub Repositories - Where to fetch code and documentation
4. Parser Configuration - What to extract from code
5. LLM Configuration - Embedding and chat model settings

1. Server Configuration

Server API Key (required)

MIMIR_SERVER_API_KEY=your-generated-api-key

This is your server's authentication key. It protects your API endpoints from unauthorized access. Generate one using npm run generate-apikey in the mimir-rag directory.

GitHub Webhook Secret (optional)

MIMIR_SERVER_GITHUB_WEBHOOK_SECRET=your-webhook-secret

When GitHub sends webhook events (like when code is pushed), this secret verifies that the request actually came from GitHub. Only needed if you want automatic ingestion when code changes in your repository.

Fallback Ingest Interval (optional)

MIMIR_SERVER_FALLBACK_INGEST_INTERVAL_MINUTES=60

If webhooks fail or aren't configured, this sets up a scheduled backup that periodically re-ingests your repositories. Useful for keeping your index fresh automatically.

2. Supabase Configuration

Supabase URL (required)

MIMIR_SUPABASE_URL=https://your-project.supabase.co

Your Supabase project's API endpoint. Mimir uses it to connect to your database and store/query vector embeddings. Find this in your Supabase dashboard under Project Settings → API → "Project URL".

Supabase Service Role Key (required)

MIMIR_SUPABASE_SERVICE_ROLE_KEY=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9...

This key gives Mimir full access to your Supabase database. It's needed to create tables, insert embeddings, and perform vector searches. Find it in Supabase dashboard → Project Settings → API → "service_role" key (not the "anon" key).

⚠️ Security Note: This key has full database access. Never commit it to version control or expose it publicly.

Supabase Table (optional)

MIMIR_SUPABASE_TABLE=docs

Default: "docs"

Specifies which table in your Supabase database stores the document chunks. Use different table names if you have multiple Mimir instances or want to separate different documentation sets.

Supabase Database Password (optional)

MIMIR_SUPABASE_DB_PASSWORD=your-database-password

Mimir can automatically construct the full database connection URL from your Supabase URL and password. If provided, Mimir combines this with MIMIR_SUPABASE_URL to create DATABASE_URL automatically.

Similarity Threshold (optional)

MIMIR_SUPABASE_SIMILARITY_THRESHOLD=0.2

Default: 0.2
Range: 0.0 to 1.0

Controls how similar a document chunk must be to your query to be included in results. Lower values (0.1-0.3) return more results but may include less relevant content. Higher values (0.5-0.8) return fewer, more precise matches.

Match Count (optional)

MIMIR_SUPABASE_MATCH_COUNT=10

Default: 10

Limits how many document chunks are returned per query. More chunks provide more context but increase API costs and response time. Fewer chunks are faster but may miss relevant information.

3. GitHub Repository Configuration

Mimir fetches code and documentation from GitHub repositories. You can configure single or multiple repositories.

Single Repository

For most projects, start with a single repository:

MIMIR_GITHUB_URL=https://github.com/your-org/your-repo
MIMIR_GITHUB_BRANCH=main
MIMIR_GITHUB_TOKEN=ghp_your_token_here

Separate Code and Documentation Repos

If your code and docs are in different repositories:

# Code repository (TypeScript, Python, etc.)
MIMIR_GITHUB_CODE_URL=https://github.com/your-org/code-repo
MIMIR_GITHUB_CODE_DIRECTORY=src
MIMIR_GITHUB_CODE_INCLUDE_DIRECTORIES=src,lib

# Documentation repository (MDX files)
MIMIR_GITHUB_DOCS_URL=https://github.com/your-org/docs-repo
MIMIR_GITHUB_DOCS_DIRECTORY=docs
MIMIR_GITHUB_DOCS_INCLUDE_DIRECTORIES=docs,guides

Multiple Repositories

For larger projects with multiple codebases or documentation sources:

# ============================================
# CODE REPOSITORIES
# ============================================
MIMIR_GITHUB_CODE_REPO_1_URL=https://github.com/your-org/repo1
MIMIR_GITHUB_CODE_REPO_1_DIRECTORY=src
MIMIR_GITHUB_CODE_REPO_1_INCLUDE_DIRECTORIES=src,lib
MIMIR_GITHUB_CODE_REPO_1_EXCLUDE_PATTERNS=*.test.ts,test/

MIMIR_GITHUB_CODE_REPO_2_URL=https://github.com/your-org/repo2
MIMIR_GITHUB_CODE_REPO_2_DIRECTORY=packages

# ============================================
# DOCUMENTATION REPOSITORIES
# ============================================
MIMIR_GITHUB_DOCS_REPO_1_URL=https://github.com/your-org/docs1
MIMIR_GITHUB_DOCS_REPO_1_DIRECTORY=docs
MIMIR_GITHUB_DOCS_REPO_1_BASE_URL=https://docs.example.com
MIMIR_GITHUB_DOCS_REPO_1_CONTENT_PATH=content/docs

MIMIR_GITHUB_DOCS_REPO_2_URL=https://github.com/your-org/docs2
MIMIR_GITHUB_DOCS_REPO_2_BASE_URL=https://docs2.example.com

4. Parser Configuration

Control what code entities get extracted and indexed from your codebase.

Extract Variables (optional)

MIMIR_EXTRACT_VARIABLES=false

Default: false

Controls whether top-level variable declarations are extracted as separate entities. If false, only functions, classes, and interfaces are indexed. If true, variables like export const config = {...} are also indexed. Useful if you have important configuration objects or constants that developers frequently search for.

Note: Exported const functions (like export const myFunction = () => {}) are always extracted regardless of this setting.

Extract Methods (optional)

MIMIR_EXTRACT_METHODS=true

Default: true

Controls whether class methods are extracted as separate entities. If true, each method becomes its own searchable entity. If false, only the class itself is indexed. Disable if you have many small methods and want to reduce index size, or if you prefer searching at the class level.

Exclude Patterns (optional)

MIMIR_EXCLUDE_PATTERNS=*.test.ts,*.spec.ts,test/,__tests__/,tests/

Prevents test files and other non-production code from being indexed. This keeps your search results focused on actual implementation code and reduces index size.

Patterns supported:

• File patterns: *.test.ts, *.spec.ts, *.d.ts
• Directory patterns: test/, __tests__/, tests/, node_modules/

Common test patterns are excluded automatically if not specified.

5. LLM Configuration

Mimir uses LLMs for two purposes: creating embeddings (vector representations) and generating chat responses. You can use different providers for each.

Embedding Configuration (required)

Embeddings convert your documentation and code into vectors that can be searched semantically.

Embedding Provider (required)

MIMIR_LLM_EMBEDDING_PROVIDER=openai

Which provider to use. Options: openai, google, mistral

• OpenAI: Fast, cost-effective, widely used. Good default choice.
• Google: Alternative option, good quality embeddings.
• Mistral: European provider, good for compliance requirements.

Embedding Model (required)

MIMIR_LLM_EMBEDDING_MODEL=text-embedding-3-small

The specific model to use. Different models have different quality/cost tradeoffs:

• text-embedding-3-small: Fast and cheap, good for most use cases
• text-embedding-3-large: Higher quality, more expensive
• text-embedding-004 (Google): Alternative option

Embedding API Key (required)

MIMIR_LLM_EMBEDDING_API_KEY=sk-your-key-here

Your API key for the chosen provider. Required to make embedding API calls.

Chat Configuration (required)

Chat completions generate natural language answers from retrieved documentation.

Chat Provider (required)

MIMIR_LLM_CHAT_PROVIDER=openai

Which provider to use. Options: openai, google, anthropic, mistral

• OpenAI: Fast, reliable, good default
• Anthropic (Claude): High quality responses, better reasoning
• Google (Gemini): Alternative option
• Mistral: European provider

Chat Model (required)

MIMIR_LLM_CHAT_MODEL=gpt-4

The specific model. Examples:

• OpenAI: gpt-4, gpt-4-turbo, gpt-3.5-turbo
• Anthropic: claude-3-opus, claude-3-sonnet, claude-3-haiku
• Google: gemini-pro
• Mistral: mistral-large

Chat API Key (required)

MIMIR_LLM_CHAT_API_KEY=sk-your-key-here

Your API key for the chosen provider.

Chat Temperature (optional)

MIMIR_LLM_CHAT_TEMPERATURE=0

Default: 0

Controls randomness (0.0 to 2.0). Lower values (0-0.3) give more deterministic, factual answers. Higher values (0.7-1.0) give more creative responses.

Mixing Providers

You can use different providers for embeddings and chat:

# Use OpenAI for embeddings (fast, cheap)
MIMIR_LLM_EMBEDDING_PROVIDER=openai
MIMIR_LLM_EMBEDDING_MODEL=text-embedding-3-small

# Use Anthropic for chat (high quality)
MIMIR_LLM_CHAT_PROVIDER=anthropic
MIMIR_LLM_CHAT_MODEL=claude-3-sonnet

This allows you to optimize for cost (cheap embeddings) and quality (better chat model) separately.

Complete Example

Here's a complete .env file example with all common settings:

# Server (Required)
MIMIR_SERVER_API_KEY=your-generated-api-key

# Supabase (Required)
MIMIR_SUPABASE_URL=https://your-project.supabase.co
MIMIR_SUPABASE_SERVICE_ROLE_KEY=your-service-role-key

# Supabase (Optional)
MIMIR_SUPABASE_DB_PASSWORD=your-db-password
MIMIR_SUPABASE_TABLE=docs
MIMIR_SUPABASE_SIMILARITY_THRESHOLD=0.2
MIMIR_SUPABASE_MATCH_COUNT=10

# GitHub - Single Repository
MIMIR_GITHUB_URL=https://github.com/your-org/your-repo
MIMIR_GITHUB_BRANCH=main
MIMIR_GITHUB_TOKEN=ghp_your_token_here

# LLM - Embeddings (Required)
MIMIR_LLM_EMBEDDING_PROVIDER=openai
MIMIR_LLM_EMBEDDING_MODEL=text-embedding-3-small
MIMIR_LLM_EMBEDDING_API_KEY=sk-your-openai-key

# LLM - Chat (Required)
MIMIR_LLM_CHAT_PROVIDER=openai
MIMIR_LLM_CHAT_MODEL=gpt-4
MIMIR_LLM_CHAT_API_KEY=sk-your-openai-key
MIMIR_LLM_CHAT_TEMPERATURE=0

Next Steps

• Learn about Deployment options
• Check the API Reference for programmatic access
• Set up MCP integration for AI assistants