PluginBench
MCP Server
Active
Apache-2.0

contextweaver MCP Server

io.github.dgenio/contextweaver

Capture, verify, and diff your agent's tool capabilities deterministically—no model required.

What is the contextweaver MCP server?

ContextWeaver is an MCP gateway and capability-management tool that creates deterministic snapshots of tool/API surfaces from OpenAPI documents, MCP tools/list responses, or native catalogs. It enables you to inspect, verify, and compare capability changes semantically before deployment, without requiring a model account or runtime executor.

ContextWeaver helps you track and review changes to your agent's available tools and capabilities. It takes snapshots of tool definitions from OpenAPI specs or MCP servers, normalizes them deterministically, and produces structured diffs that highlight breaking changes, additions, and documentation-only updates. This is useful for teams that want to commit capability contracts to version control and catch unintended API surface changes before they reach production.

How to install contextweaver

Copy-paste configuration for popular MCP clients.

transport: stdio
Config generated by PluginBench — verify against the source before use.
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "contextweaver": {
      "command": "uvx",
      "args": [
        "contextweaver",
        "mcp",
        "serve",
        "--config"
      ]
    }
  }
}

Tools & capabilities

Tools this server exposes to the agent.

  • snapshot — Create a deterministic normalized snapshot of capabilities from OpenAPI documents, MCP tools/list responses, or native catalogs.
  • inspect — Examine the structure and contents of a capability snapshot.
  • verify — Validate a D1 snapshot contract: structure, deterministic ordering, logical-ID uniqueness, and canonical capability digest.
  • diff — Compare two capability snapshots and report semantic changes, separating breaking contract changes from documentation-only updates.

Use cases

  • Commit tool capability contracts to Git and review changes before deploying agent updates
  • Detect unintended breaking changes to OpenAPI or MCP tool schemas
  • Compare capability surfaces across different versions of an API or tool set
  • Verify that tool definitions are deterministically normalized and logically unique
  • Identify which changes are breaking (e.g., required field additions) versus safe (e.g., description updates)

contextweaver MCP server FAQ

What is ContextWeaver D1?

D1 is a capability-snapshot and semantic-drift experiment. It creates deterministic snapshots of tool/API surfaces and produces structured diffs showing what changed, without executing tools or requiring a model account.

Is ContextWeaver free?

Yes. ContextWeaver is open-source under the Apache-2.0 license and available on PyPI.

How do I install ContextWeaver?

Install via pip: `pip install contextweaver`. Then use the CLI via `python3 -m contextweaver.d1 snapshot|inspect|verify|diff`.

What sources does ContextWeaver support?

ContextWeaver accepts OpenAPI documents, captured MCP `tools/list` JSON responses, and native ContextWeaver catalogs as input sources.

Does ContextWeaver require authentication or API keys?

No. ContextWeaver is a deterministic offline tool for snapshot creation and comparison. It does not execute tools, call APIs, or require credentials.

Is ContextWeaver production-ready?

ContextWeaver is in alpha as a product experiment. The implementation is tested and works, but the project is actively measuring whether users retain it after trying it on real projects.

README (reference)

Source of truth, from the repository.

contextweaver

<!-- mcp-name: io.github.dgenio/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.

git clone --depth 1 https://github.com/dgenio/contextweaver.git
cd contextweaver
python3 -m pip install .

Run the maintained OpenAPI example:

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

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

After the API changes:

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

Captured MCP tools

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

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

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:

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:

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

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.

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