Limitless Library

Reuse work without giving up trust

AI agents repeatedly solve problems that another agent has already solved. That wastes time and compute. Search alone does not make an earlier result safe to reuse: its authorization, compatibility, integrity, and actual adoption still need proof.

Limitless Library lets agents check before starting from scratch. It returns one permissioned result that fits the receiving environment—an exact component or source-free method—or abstains without disclosing a candidate. The receiver decides what may enter, verifies it locally, and records evidence that adopted work was actually used.

Related MCP server: io.github.yugantm/hvtracker-mcp

At a glance

Quick start

Try the complete local lifecycle from a source checkout. You need Python 3.11 or newer and Bubblewrap on Linux. On Debian or Ubuntu, install the one system dependency if it is not already present:

sudo apt-get install bubblewrap

Then run:

git clone https://github.com/Univeracity/limitlesslibrary.git
cd limitlesslibrary
./scripts/limitless

That is the only project command required. On first use, the launcher creates an isolated environment under .limitless/, installs the small Python dependency set, runs exact adoption, method guidance, and safe abstention, and retains inspectable evidence under .limitless/quickstart. It requires no environment activation, account, cloud service, model API, or model download. The initial dependency installation may require package-index access; the lifecycle itself runs without network access.

Check host readiness or retain another run at a path you choose:

./scripts/limitless doctor
./scripts/limitless demo --workspace ./limitless-demo

The demo refuses to overwrite an existing workspace. Later launcher runs reuse the isolated environment; running it without arguments keeps the original quick-start evidence and performs a disposable replay.

When integrating Limitless into another environment, install the checkout with python -m pip install .; the installed commands are limitless and limitless-mcp.

What the demo does

The bundled demo performs useful work on a structured agent audit event. It installs a narrow field-name redaction component and returns a sanitized copy while preserving non-sensitive data. It then demonstrates every safe outcome:

1. Exact adoption — installs exact bytes without overwrite, runs receiver-owned checks, and proves receiver code invoked the component.

2. Method guidance — returns a source-free method when Python bytes do not fit a JavaScript receiver.

3. Safe abstention — withholds candidate details when no result fits.

The redactor protects configured structured field names; it is not a general scanner for secrets embedded in free text. See the local demo evidence map for the generated artifacts and manual inspection commands.

How verified reuse works

For exact reuse, the receiver—not the capsule—controls the trust boundary:

1. A query describes the requested capability and receiving environment.

2. Policy and compatibility gates select at most one eligible result.

3. The receiver chooses the destination and provides digest-bound checks.

4. Limitless installs content-addressed bytes without overwriting receiver files.

5. Bubblewrap runs the checks with no network, no inherited secrets, bounded resources, and a read-only receiver mount.

6. Runtime evidence proves invocation and an append-only receipt binds the decision, component, verification, and disposition.

If exact bytes do not fit, only a source-free method may cross. If no safe candidate exists, Limitless abstains without disclosing one.

What is open here

• JSON Schemas for capsules, queries, decisions, receiver recipes, verifier results, and adoption receipts.

• A source-minimized local catalog with policy and compatibility checks.

• Exact-byte, no-overwrite installation with rollback on failure.

• Receiver-owned adherence and obligation verification under Bubblewrap.

• Python embedding and bounded stdio MCP connector surfaces.

• Authoring and sealing commands, a one-command demo, conformance fixtures, and tests.

This repository is the inspectable foundation of the Limitless product. Its trust and foundation commitments are described in Open-source foundation.

Manual conformance proof

The smaller examples/ fixture exposes each primitive separately:

limitless validate-catalog --catalog examples/catalog

limitless query \
  --catalog examples/catalog \
  --request examples/requests/exact-python.json

Continue through installation, method guidance, abstention, and authoring in the conformance example.

MCP

Start the bounded local stdio server:

limitless-mcp --catalog examples/catalog

It exposes limitless_query_before_work and supports stateless MCP 2026-07-28 requests plus the legacy 2025-03-26 initialization flow. MCP is a decision channel, not an artifact transport; installation remains an explicit receiver-local operation.

Python callers can use query_local(...) or McpStdioConnector. See Protocol.

Authoring

The checked-in examples/authoring records omit derived digests. Seal them only after payload and receiver-verifier review:

limitless seal-capsule \
  --draft examples/authoring/capsule.draft.json \
  --root examples/catalog/hello-component \
  --output capsule.json

limitless seal-recipe \
  --draft examples/authoring/recipe.draft.json \
  --receiver examples/receiver \
  --output recipe.json

Outputs are immutable: both commands refuse to overwrite an existing path.

Documentation

Status and security

This is a pre-alpha reference implementation. It is intentionally local, single-operator, and Linux-only for contained verification. It is not yet a remote trust system or package manager, and technical integration is not treated as product adoption.

There is deliberately no unsandboxed verifier fallback. Querying and method selection work without Bubblewrap; exact adoption fails closed if containment is unavailable. Schemas and interfaces may change incompatibly before 0.1.0 stable.

Read the trust model before use. Report vulnerabilities according to SECURITY.md.

Contributing and license

Contributions should preserve fail-closed behavior, non-disclosure on abstention, and receiver ownership of verification. Start with CONTRIBUTING.md and the Code of Conduct.

Apache-2.0 licensed. See LICENSE and NOTICE.