pond

Lossless storage and hybrid search for AI agent sessions, across every agentic client.

Quickstart. Install, ingest your local sessions, and add pond as an MCP server in any app:

brew install tenequm/tap/pond
pond sync

# add pond as an MCP server (pick your client):
claude mcp add -s user pond -- pond mcp   # Claude Code
codex mcp add pond -- pond mcp            # Codex

Pond keeps every AI conversation you've ever had intact and searchable, and lets you continue any of them in any supported tool. Your history, your search, your sessions - independent of the agent vendor that made them.

One Rust binary that ingests sessions from any agentic client (Claude Code, Codex, and more on the roadmap) into a canonical Session / Message / Part interlingua, stores them in Lance on object storage, and serves hybrid search over them via HTTP+JSON and MCP. Two deployments: a personal pond on your laptop, or a multi-tenant backend for hosted agent infrastructure. No SQL, no extra database, no wrapper around Lance.

Status: pre-v1. Schemas, wire shapes, and config keys are subject to breaking change until v1. See docs/spec.md.

Table of Contents

• Background
• Install
• Usage
• Design
• References
• Contributing
• License

Background

Every agentic CLI ships its own session format and its own search surface. Switching tools means losing history. Replaying a Claude Code session in another provider's tooling means re-translating the wire shape by hand. Hosted multi-tenant deployments rebuild the same storage layer from scratch.

Pond is the storage and retrieval layer that sits underneath. Every adapter is a bidirectional codec between a client format and one canonical schema, so any session can be restored by any adapter - it need not return to the client that produced it. Storage, hybrid search (BM25 + vector, score-normalized fusion), and provider-agnostic replay all sit on a single Lance-on-object-storage foundation.

The v1 surface includes: full CLI, HTTP+JSON and MCP transports, hybrid search over three Lance datasets, intfloat/multilingual-e5-small embeddings at FP16 weights (Metal on macOS, CUDA opt-in, CPU fallback), and local-FS / S3 / GCS / Azure backends through Lance's object_store integration.

Install

Linux and macOS are supported; Windows is not in v1 scope.

Package Managers (macOS and Linux):

brew install tenequm/tap/pond                       # Homebrew
nix profile add github:tenequm/nur-packages#pond    # Nix
cargo install pond-db                               # crates.io (installs the `pond` command)

Build from source:

git clone https://github.com/tenequm/pond.git
cd pond
cargo install --path .

For CUDA acceleration on Linux:

cargo install --path . --features cuda

On macOS the Metal backend is selected automatically; on other systems the CPU fallback runs without extra features.

Usage

Import sessions from local sources, embed them, update indexes, and search:

pond sync
pond search "how did we wire up the OCC retry loop"

Run a server:

pond serve                         # HTTP on 127.0.0.1:9797
pond serve --transport stdio       # MCP over stdio
pond mcp                           # alias for stdio MCP

Fetch a single session or message, or move a whole corpus:

pond get --session-id <id>
pond export -o snapshot.pond
pond import snapshot.pond

Stages can be run independently when needed:

pond sync --only import
pond sync --only embed
pond sync --only update-indexes
pond sync --import-from snapshot.pond

pond status reports row counts, storage size, embedding coverage, and index health. It prints quick storage information first, then finishes the longer checks in front of the user. pond search --explain returns Lance's analyze_plan output for each retrieval arm.

Design

The full contract is in docs/spec.md. Key choices:

• Lance direct, no wrapper. The lance-format/lance crates are the only storage and search engine. No lancedb, no SQL, no parallel abstraction. Storage, indexing, OCC, schema evolution, blob columns, versioning, and time-travel are all Lance.
• Canonical Session / Message / Part interlingua. Owned in pond, in the shape of Effect v4's Prompt-side Part union. This schema is pond's product; everything else is machinery around it.
• Three Lance datasets (sessions, messages, parts). messages carries the nullable embedding (vector + embedding_model) alongside denormalized filter columns (source_agent / project / role / timestamp) for single-stage filter pushdown.
• No-synthesis adapter seam. Adapters parse source records through extractor helpers that make "invent a value" a compile error - model-no-synthesis, model-schema-honesty, and adapter-provenance-required are structural, not review rules.
• Index lifecycle decoupled from writes. Writes commit data without folding indexes. pond sync runs index maintenance by default, and pond sync --only update-indexes runs it on demand; Lance merges index results with a flat scan over unindexed fragments, so reads stay correct.
• Score-normalized hybrid fusion. Per-arm shaping (max-norm BM25 for FTS, rank-norm for vector), min-max to [0, 1], then weighted sum. Session-root-keyed dedup so cross-arm agreement compounds at the conversation level.
• Language-neutral full-text. Character ngram tokenizer (3-5), no monolingual stemmer - pond indexes sessions in any language alike.
• Two transports, one handler set. HTTP+JSON (axum) and MCP (rmcp) both dispatch into the same handlers. Wire ops: pond_search, pond_get, pond_ingest, pond_session_events. MCP also exposes schema://pond and stats://pond resources.
• Opaque-string multi-tenancy. Each tenant is a namespace string the integrator supplies; pond does not authenticate, authorize, or model identity. The object store's IAM is the storage boundary.
• Encryption is operational. Bucket SSE plus filesystem encryption; pond holds no keys and adds no application-level crypto.

References

docs/references/ holds frozen snapshots of upstream schemas; real session captures live under tests/fixtures/adapter/. Each subdirectory's README pins the source URL, the upstream commit, and the snapshot date.

Contributing

Issues and pull requests are welcome. The most useful contributions right now:

• Spec feedback on docs/spec.md.
• Pointers to additional reference schemas or session samples worth snapshotting under docs/references/.
• Bug reports against the v1 surface (CLI verbs, wire ops, schema mismatches, OCC behavior, object-store backends).

For larger changes, open an issue first to discuss the direction. For security issues, see SECURITY.md.

License

Apache-2.0 (c) 2026 tenequm