flameox
Bounded local runtime evidence for coding agents.
Flameox coordinates profilers, benchmark tools, trace processors, and direct local targets. It turns an explicit artifact or command into bounded evidence while keeping durable preservation optional. The agent chooses hypotheses and experiments; Flameox records observed inputs, execution provenance, typed evidence, coverage, and limitations.
There is no workspace to initialize or project configuration to maintain. Pass exact artifact paths to analysis and an explicit argv plus absolute working directory to capture. Flameox does not search parent directories, edit project files, or provide a hosted service.
Quick start
Configure an MCP client with the global setup command:
npx flameox@latest setup
Setup detects supported clients and asks which configurations to update. For automation, select
clients explicitly, for example --client codex --yes or --all --yes; --dry-run reports the
paths and actions without writing. Setup preserves unrelated client configuration and does not
change project files. See the npm package guide for details.
For direct CLI use, pass exact artifact paths or an explicit command:
uvx flameox analyze artifact.preview /absolute/path/to/artifact.json
uvx flameox capture --provider direct --cwd "$PWD" -- python benchmark.py
To launch the stdio MCP server manually:
uvx flameox mcp serve
For local development, clone the repository, install its development dependencies, and inspect the available tools:
git clone https://github.com/morluto/flameox.git
cd flameox
uv sync --extra dev --extra memory --extra trace --extra cpu
uv run flameox mcp inspect
Evidence and storage
Analysis and unpreserved capture use bounded session scratch. Session analysis_id values expire
when evicted or when the server stops. Explicit preservation creates the user-level Flameox data
directory and stores native bytes and a canonical evidence bundle by SHA-256. Set
FLAMEOX_DATA_DIR to choose another location. Preservation is optional; it does not imply full
console-output retention.
Flameox distinguishes observed, derived, and inferred claims. Profiles guide exploration but do not establish causality or performance improvement. Confirmatory claims require representative workloads, declared metrics and estimands, compatible identities, preserved samples, and a semantic oracle.
MCP
The MCP server has no workspace binding. It exposes named analysis and capture tools through the
same capability registry as the CLI. Analysis tools accept explicit sources; capture tools accept
a typed target and provider. Tool schemas expose capability-specific fields directly. Inspect the
catalog with flameox mcp inspect; use --capability CAPABILITY_ID or --tool TOOL_NAME for
focused schemas and examples. The complete contract and current tool catalog are in
the interface guide.
Capture takes argv, not a shell string. A direct target supplies an absolute working directory and
bounded environment overrides. Results may include next_page; replay its named analysis tool
and arguments unchanged. Capture continuations read collected artifacts and do not rerun the
target. MCP work belongs to the live request, so cancellation applies directly and no detached job
survives a restart.
Documentation
- Architecture describes process and package boundaries.
- Storage and evidence defines preservation and provenance.
- Investigations covers experiments, comparison, and evidence quality.
- Adapters documents provider compatibility and integration policy.
- Runtime safety covers limits, recovery, integrity, and privacy.
- Interfaces defines CLI and MCP contracts.
- Testing describes test selections and known proof gaps.
Development
Flameox requires Python 3.12 or newer and uses the committed uv.lock. See
CONTRIBUTING.md for development setup and contribution guidance.
uv run ruff check src tests tools
uv run ruff format --check src tests tools
uv run mypy src tests tools
uv run pytest -q
Flameox is licensed under the MIT License.
Metadata
Release files for flameox 0.2.8
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| flameox-0.2.8.tar.gz | 17.2 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| flameox-0.2.8-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 17.4 MB
Release files / flameox-0.2.8.tar.gz
| Download URL | flameox-0.2.8.tar.gz |
|---|---|
| Size | 17.2 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
|
BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 9, 2026.
Transparency logRelease files / flameox-0.2.8-py3-none-any.whl
| Download URL | flameox-0.2.8-py3-none-any.whl |
|---|---|
| Size | 242.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
b6dcebf0c339cf1eaad57b7574d7ebe629bf6ed671e0bfe6603113527816c53d
|
|
BLAKE2b-256 checksum How to use checksums |
e252df461d05a83155bde9a121858174e429d767ee9a0f9a8d69f4792bf33bed
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 9, 2026.
Transparency log