Configure Mash

Start with the TOML file created by mash init. Run mash status to see its resolved location, or select a file explicitly with mash --config PATH status. Use TOML for this file.

Choose histories and an age limit

Each configured provider is enabled. Roots must be absolute paths to that provider’s history, not to the source-code project you want to search.

version = 1

[providers.codex]
roots = ["/home/you/.codex/sessions"]

[providers.claude-code]
roots = ["/home/you/.claude/projects"]

[index]
since_days = 90
destination = "local"

Use the paths detected on your machine by mash init or mash status --installation; the paths above are examples. Original provider files are never modified.

To include all ages permanently, replace since_days = 90 with all_history = true. Do not set both. One-off indexing flags such as --all-history override the configured age selection.

Local Qdrant

The defaults use HTTP port 6333 and gRPC port 6334 on localhost. For an existing service at another address, edit:

[qdrant]
url = "http://127.0.0.1:6333"
grpc_url = "http://127.0.0.1:6334"
memory = "durable"
# api_key_env = "MASH_LOCAL_QDRANT_KEY"

Both endpoints must reach the same Qdrant 1.19+ instance. If an API key is required, put it in the named environment variable, not in the URL.

Search defaults

[views.query]
unit = "chats"
limit = 20
intent = "exact-mention"

CLI and MCP arguments override these defaults for one request. Query defaults take effect without rebuilding. To search by meaning, follow semantic model setup; changing intent alone does not create dense search data.

Share across your machines

A local-only setup needs no [shared] table. To publish as well, follow multi-machine setup, add its connection settings, and set [index] destination = "both".

Each machine publishes its own indexed history. Use a different node ID and token on each machine, with the same group ID and server URL.

Remote embeddings

Search runs locally by default. Remote embeddings send history text and queries to your chosen provider. Add embeddings to the node configuration to use Voyage-4 for both document and query embeddings:

[embeddings]
api = "voyage"
url = "https://api.voyageai.com/v1/embeddings"
model = "voyage-4"
dimensions = 1024
token_env = "VOYAGE_API_KEY"

Set VOYAGE_API_KEY in the environment where you run Mash. Use a model and size supported by your provider. For an OpenAI-compatible service, use api = "openai-compatible" and its complete embeddings URL.

After changing embedding settings, run mash models install to install the local reranker, then mash index to prepare your history. Enable semantic search as described in model setup. For a shared setup, coordinate model changes with the server administrator.