contextweaver

io.github.dgenio由 GitHub 账号 dgenio 发布v0.18.2更新于 Oct 24, 2026

MCP gateway: bounded tool shortlists + artifact-backed result firewall. Deterministic, no model.

已验证STDIO仅桌面开发者工具AI 与机器学习

概览

AI 生成的概览

一个本地、确定性的 MCP 网关实验,可从 OpenAPI、MCP tools/list 或原生目录捕获智能体的能力面,并通过对比发现漂移

可以做什么
从 OpenAPI 文档、已捕获的 MCP tools/list 响应或原生目录生成确定性的能力快照,无需模型账号或网关。检查并校验快照的结构、排序、逻辑 ID 唯一性和规范摘要。对比基线与候选快照,区分新增、移除的能力与既有能力的变化,并区分契约变更与仅文档变更。将 required、type、enum 等字段的变更标记为可能破坏兼容,供人工审查。
适用场景
当 API 或 MCP 工具面变化较频繁,普通 Git diff、配置审查和测试已不足以让能力变化一目了然,且希望在部署前保留提交的产物和语义漂移报告时值得一试。README 本身建议:工具面很小且很少变化,或需要智能体循环、工具执行器、IAM 层或生产编排器时,不要添加它。
运行要求
需要本地 Python 环境;README 说明支持 Python 3.10–3.14,可用 pip 安装该包或直接运行模块。输入为本地 OpenAPI 文档、保存的 MCP tools/list JSON 响应或原生目录文件。不需要模型账号、API 密钥、网关或工具执行器。
安装前请注意
项目自称为 alpha 阶段的产品实验,用户价值假设尚未证实,且处于 1.0 之前,依赖历史运行时 API 前应查看变更日志。可能破坏兼容的标记刻意保守,并非完整的 JSON-Schema 兼容性检查器。verify 只检查快照契约,不代表部署批准、安全认证、身份验证或实现正确性。README 要求不要在公开报告中包含凭据、客户数据、专有模式或私有提示词。

安装

在 SourceWeft 中

  1. 打开 控制台中的 contextweaver,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

README

contextweaver

[CI] [PyPI version] [Python versions] [License: Apache-2.0] [OpenSSF Scorecard] [Docs] [GitHub Discussions]

Capture an agent's effective capability surface, commit it, and see semantically meaningful changes before deployment.

ContextWeaver is currently testing a deliberately narrow product hypothesis: capability snapshot + semantic drift.

Given an OpenAPI document, a captured MCP tools/list response, or a native ContextWeaver catalog, the D1 experiment produces a deterministic normalized snapshot that you can inspect, verify, and compare with a later candidate. It does not require a model account, a gateway, a tool executor, or the Weaver Stack.

Status: alpha, and specifically a product experiment. The implementation works and is tested; the user-value hypothesis is not yet proven. The project is actively measuring whether independent users keep this workflow after trying it on real projects.

Try the capability-drift experiment

Clone the repository and install that checkout so the maintained example fixtures and the code under evaluation are guaranteed to match:

Commands below use python3, matching the repository's documented default (docs/agent-context/workflows.md). On Windows installations that expose Python through the launcher, replace python3 with py -3; if your environment already exposes the intended interpreter as python, use that consistently.

bash
git clone --depth 1 https://github.com/dgenio/contextweaver.gitcd contextweaverpython3 -m pip install .

Run the maintained OpenAPI example:

bash
python3 -m contextweaver.d1 snapshot examples/d1/openapi_before.json --source-type openapi --output ./cw-before.jsonpython3 -m contextweaver.d1 snapshot examples/d1/openapi_after.json --source-type openapi --output ./cw-after.jsonpython3 -m contextweaver.d1 inspect ./cw-after.jsonpython3 -m contextweaver.d1 verify ./cw-after.jsonpython3 -m contextweaver.d1 diff ./cw-before.json ./cw-after.json

The candidate fixture intentionally:

  • makes customer_id required on the existing listInvoices capability;
  • changes its description;
  • adds a new getInvoice capability.

The diff separates capability additions/removals from changes to an existing logical capability and reports the structured paths that changed. Contract changes are separated from documentation-only changes. Changes involving fields such as required, type, or enum are flagged as potentially breaking for review.

That flag is intentionally conservative: ContextWeaver does not claim to be a complete JSON-Schema compatibility checker.

Full walkthrough: Capability drift experiment.

Use it on your own source

OpenAPI

bash
python3 -m contextweaver.d1 snapshot ./openapi.yaml --source-type openapi --output ./capabilities.jsonpython3 -m contextweaver.d1 verify ./capabilities.json

After the API changes:

bash
python3 -m contextweaver.d1 snapshot ./openapi.yaml --source-type openapi --output ./capabilities-candidate.jsonpython3 -m contextweaver.d1 diff ./capabilities.json ./capabilities-candidate.json

Captured MCP tools

If you already have an MCP tools/list response saved as JSON:

bash
python3 -m contextweaver.d1 snapshot ./tools-list.json \  --source-type mcp \  --output ./capabilities.json

For MCP, D1 compares tools by their upstream logical name so an input-schema edit appears as a change to the same capability rather than an unexplained remove/add pair. The historical schema-sensitive routing ID is retained separately as normalized_id for inspection.

Capturing a live MCP server is a separate operation. snapshot, inspect, diff, and verify do not execute discovered capabilities.

Native ContextWeaver catalog

bash
python3 -m contextweaver.d1 snapshot ./catalog.json \  --source-type native \  --output ./capabilities.json

What verify means

verify checks the D1 snapshot contract: structure, deterministic ordering, logical-ID uniqueness, and the canonical capability digest.

It is not:

  • deployment approval;
  • security certification;
  • authentication or authorization;
  • a guarantee that a tool implementation is correct;
  • routing-quality evaluation;
  • production runtime attestation.

When not to use ContextWeaver D1

A negative answer is useful evidence for this project. Do not add ContextWeaver just because capability snapshots sound tidy.

Use something simpler when:

  • ordinary Git diff, config review, and tests already make your capability changes obvious;
  • your tool/API surface is tiny and rarely changes;
  • provider-native tool search is the only problem you are trying to solve;
  • you need an agent loop, tool executor, IAM layer, or production orchestrator;
  • maintaining another committed artifact costs more than the review/debugging problem it removes.

If you try D1 and conclude that Git/tests are cheaper, that is a valid product result — please say so.

What is being tested

The current survival experiment asks a stronger question than whether the code works:

Do capability snapshots and semantic drift reports improve a real review/manual/risk process enough that independent users keep them?

The project distinguishes:

text
qualified exposure  -> understood the problem  -> chose to evaluate  -> attempted setup  -> reached first useful output  -> used on a real project  -> retained independently / removed

Stars, forks, downloads, a successful demo, and maintainer-created integrations are not treated as retained adoption.

The controlling product decision is tracked in #758, and the distribution quality gate is #855. Unassisted first success and retention are tracked in #658 and genuine adoption in #551.

What about routing, context compilation, and the MCP gateway?

ContextWeaver already contains substantial historical runtime functionality. That code still exists and currently shipped behavior should remain truthful and safe, but existing implementation is not evidence that the project should keep expanding it.

Two broader hypotheses are explicitly evidence-first:

  • D2 — bounded / phase-aware context compilation: conditional. It must show consequential value beyond contemporary provider/runtime-native mechanisms.
  • D3 — custom deterministic tool selection: a falsification track. It must beat modern provider-native tool search/deferred loading or a simple retrieval baseline on something target users actually care about.

During the D1 experiment, the project is not expanding routing sophistication, runtime bundle machinery, memory/session surfaces, framework breadth, gateway scope, vector stores, or model-assisted enrichment without a concrete external blocker or approved falsification experiment.

If you are maintaining an existing integration that uses those historical surfaces, the relevant documentation remains available:

Evidence and claims

The D1 implementation supports scoped engineering claims such as deterministic snapshot construction under the documented source/adapter contract and structured semantic-diff output. It does not yet support the stronger claim that users need or retain the product.

The historical token-reduction headline is intentionally not used to sell D1. The current evidence-integrity work for those older benchmark claims is tracked in #841.

See Claims & evidence for the claim registry and Capability drift experiment for the exact D1 contract and limitations.

Python API stability

D1 is intentionally exposed through:

bash
python3 -m contextweaver.d1 ...

rather than being promoted immediately into the historical top-level CLI or a large new public Python API. That is deliberate. The experiment should earn a permanent surface through real retained use before the project takes on another compatibility obligation.

Part of the Weaver Stack — optionally

ContextWeaver can be used standalone. It has no hard dependency on the sibling Weaver projects.

The wider Weaver Stack contains adjacent experiments/components for planning, execution boundaries, guardrails, lessons, and evaluation. That ecosystem is not required to evaluate D1, and Stack coherence is not a reason to preserve a ContextWeaver feature that does not justify itself independently.

See the Ecosystem map only if you actually need those adjacent responsibilities.

Install and compatibility

bash
pip install contextweaver

Python 3.10–3.14 are covered by the repository CI matrix.

Current package version: 0.18.2

ProjectRelease
ContextWeaver (this repo, v0.18.2)current package release

The repository is pre-1.0. Prefer the latest supported patch release for bug and security fixes, and check the changelog before relying on historical runtime APIs.

Current roadmap

The roadmap is intentionally a product-decision sequence, not a feature queue.

MilestoneStatusMeaning
v0.18.1 — D1 survival experiment baseline✅ completeOffline snapshot/inspect/diff/verify exists; user value remains unverified.
v0.18.2✅ current (v0.18.2)D1 survival experiment and release-path recovery
D1 distribution gate🔬 evidence firstMake the front door understandable, recruit qualified evaluators, measure first success and retention.
D1 decision⏸ next decisionContinue, shrink further, or kill based on retained value after competent distribution.
D2 / D3🧪 conditionalRun only if D1 evidence or independent problem discovery justifies bounded falsification experiments.

A green CI run does not advance this roadmap by itself.

Contributing

The most valuable contributions during the survival experiment are narrow and evidence-linked:

  • a real D1 evaluator blocker;
  • a semantic-diff case that is currently misleading or silently lost;
  • deterministic normalization correctness;
  • security/release maintenance for behavior the package still ships;
  • negative evidence showing a simpler alternative wins.

Please do not add a framework adapter, routing policy, storage backend, runtime phase, or ecosystem integration solely for completeness.

See CONTRIBUTING.md and AGENTS.md for repository engineering conventions.

Security

See SECURITY.md for supported-version and vulnerability-reporting guidance. Do not include credentials, customer data, proprietary schemas, or private prompts in public adoption/evaluation reports.

Documentation

License

Apache-2.0. See LICENSE.

来源:README.md,提交 d1ceb47

工具

0
SourceWeft 尚未在沙箱中启动过该软件包,因此其工具未知。

版本历史

1
  1. v0.18.2最新Sep 16, 2026

评分

已满足适用检查项的 50%

该评分衡量此收录条目的完整程度,依据注册中心条目、端点与公开来源计算得出。它不是对服务器本身的评价,也不表示服务器安全或当前可用:可连通性是带日期的检查结果,评分也不包含安装量或用户评价。

  • 近 30 天内可连通25 分

    请保持端点能够响应 MCP 握手;SourceWeft 每 30 天探测一次。

  • 已声明认证方式10 分

    请在注册中心条目中声明凭据请求头,或保持端点能够响应探测,以便判定其认证方式。

  • 已列出工具15 分

    请让服务器在无凭据时响应 tools/list,或发布可在沙箱中无凭据启动的软件包。

  • 描述必需15 分
  • 图标10 分
  • 文档15 分
  • 许可证10 分