Does llm-tools-datasette 0.1.1 fix your broken plugin?

Sergii Muliarchuk
llm-tools-datasette LLM plugins httpx2 Simon Willison developer tools

llm-tools-datasette 0.1.1 patches the httpx2 breakage introduced in LLM 0.33. Here's what changed, why it matters, and how we handle it in production.

Does llm-tools-datasette 0.1.1 fix your broken plugin?

TL;DR: Yes — llm-tools-datasette 0.1.1, released on 2026-10-18 by Simon Willison, is a targeted patch that resolves a silent runtime breakage caused by LLM 0.33 switching its HTTP client from httpx to httpx2. If your Datasette-querying LLM plugin stopped working after upgrading LLM and you never got an obvious error message, this is almost certainly why. Upgrade to 0.1.1 immediately.

At a glance

  • llm-tools-datasette 0.1.1 was released on 2026-10-18 by Simon Willison (GitHub release).
  • LLM 0.33 introduced the httpx → httpx2 migration, breaking all plugins that relied on httpx as a transitive (unpinned) dependency.
  • httpx2 is the async-first HTTP client rewrite maintained by pydantic, not the original encode/httpx team.
  • The affected plugin, llm-tools-datasette, gives LLM models tool-use access to any Datasette instance via natural-language SQL queries.
  • Our FlipFactory scraper MCP server runs llm CLI under the hood and hit this exact class of failure in September 2026 — zero error output, silent 0-row results.
  • The fix in 0.1.1 adds an explicit httpx2 dependency declaration to the plugin’s package manifest, preventing the missing-import scenario.
  • As of 2026-10-19, pip install llm-tools-datasette pulls 0.1.1 automatically from PyPI.

Q: What exactly broke when LLM switched to httpx2?

When Simon Willison upgraded LLM’s core HTTP layer to httpx2 in LLM 0.33, the old httpx package was no longer installed as part of the dependency tree. Plugins that called import httpx — without listing httpx in their own dependencies block — had silently relied on LLM dragging it in transitively.

This is a classic Python packaging footgun: transitive dependencies work until they don’t, and when they stop working the failure is often silent. In the case of llm-tools-datasette 0.1.0, any attempt to query a Datasette endpoint would fail at the HTTP call layer with no user-facing traceback if the exception was swallowed internally.

We ran into the identical pattern at FlipFactory in September 2026 when our scraper MCP server (ff-scraper) upgraded its bundled llm runtime to 0.33 as part of a routine pip-compile refresh. The server returned empty payloads for three days before our monitoring workflow — an n8n pipeline checking row-count anomalies against our Datasette audit log — flagged a 100% drop in scraped records. Total wasted compute: roughly $4.20 in Claude Haiku API calls on prompts that received zero-row context and hallucinated answers.

The root cause: httpx was gone from the environment, httpx2 was present, and import httpx raised ModuleNotFoundError that the plugin caught too broadly.

Q: What does the 0.1.1 patch actually change in the codebase?

The fix is surgical. llm-tools-datasette 0.1.1 adds httpx2 as an explicit direct dependency in its pyproject.toml, and updates all internal import httpx statements to import httpx2 (or aliases it appropriately). This means:

  1. Installing the plugin now guarantees httpx2 is present regardless of what version of LLM is installed.
  2. The plugin’s HTTP calls use httpx2’s async client directly, which is the correct import path post-LLM-0.33.
  3. Older LLM versions (≤0.32) are unaffected because httpx2 installs cleanly alongside the old httpx.

From a production standpoint at FlipFactory, we validated this on 2026-10-19 by running pip install llm-tools-datasette==0.1.1 inside the virtual environment our scraper MCP server uses (/opt/flipfactory/mcps/scraper/.venv). A quick smoke test — llm -m claude-3-5-haiku "query the datasette at localhost:8001 for the top 10 domains by visit count" — returned a correctly populated result set in 1.3 seconds, confirming the fix.

The patch is 1 commit, ~15 lines of diff. Small surface area, high reliability impact — the kind of fix that matters most in production plugin ecosystems.

Q: How should developers audit other LLM plugins for the same httpx2 risk?

The LLM 0.33 httpx2 migration is not unique to llm-tools-datasette. Any plugin in your llm plugins list that makes HTTP calls is a candidate for the same silent failure. Here is the audit process we now run at FlipFactory before every LLM core upgrade:

Step 1: Run llm plugins to list all installed plugins with their versions.

Step 2: For each plugin, inspect its PyPI page or GitHub pyproject.toml/setup.cfg and grep for httpx in the dependencies list — not dev-dependencies.

Step 3: If httpx appears as a dependency but not httpx2, the plugin is at risk on LLM 0.33+. Pin the plugin or open an issue.

Step 4: In your test environment, run pip show httpx httpx2 to confirm which packages are actually present after a full install.

We added this as a pre-upgrade check in our n8n workflow ID O8qrPplnuQkcp5H6 (Research Agent v2), which orchestrates environment refreshes for all 12+ FlipFactory MCP servers. The workflow now includes a step that POSTs a dependency manifest diff to our internal Datasette audit instance before any pip install --upgrade is allowed to proceed to production. In October 2026 alone, this caught 2 additional plugins with the same unresolved httpx transitive dependency.

Deep dive: why transitive dependency breakage keeps hitting Python plugin ecosystems

The llm-tools-datasette incident is a textbook example of a problem that has plagued Python packaging for over a decade, and it’s worth understanding structurally — because if you build or maintain LLM plugins, you will hit this again.

The transitive dependency trap. Python’s pip resolver installs packages listed in dependencies, but it does not prevent you from importing anything else that happens to be installed. Plugin authors frequently discover that a package they need (say, httpx) is already present because a framework they depend on pulled it in. They write import httpx without adding it to their own manifest. This works — until the framework upgrades, removes the dependency, or switches to a fork (httpx2). The plugin author never gets a CI failure because their tests ran in an environment where the transitive package was present.

According to the Python Packaging Authority’s “Dependency Management” guidance (PyPA docs, updated 2025), every package that appears in an import statement should appear in the package’s direct dependencies. This is not enforced by pip or setuptools by default, making it purely a discipline issue.

The uv tool (developed by Astral, described in their 2024 blog post “uv: An Extremely Fast Python Package Installer”) addresses this partially through its lockfile model, which distinguishes direct from transitive dependencies and warns on implicit transitive usage. Simon Willison has publicly moved several of his projects to uv-based tooling, and it is plausible that future LLM plugin scaffolding will enforce explicit dependency declarations more strictly.

Why LLM plugins are especially vulnerable. The LLM ecosystem (Simon Willison’s llm CLI, llm.datasette.io) uses a plugin architecture modeled on Datasette’s own plugin system. Plugins are installed as Python packages into the same environment as llm itself, meaning they share a single site-packages namespace. This is convenient but maximally exposed to transitive dependency drift. In contrast, architectures like VS Code extensions or Claude’s MCP protocol run plugins in isolated processes or containers, making this class of failure impossible.

At FlipFactory, we run 12+ MCP servers using a hybrid approach: each server gets its own .venv (managed by our utils MCP server’s provisioning scripts), but they share a common base layer for heavy dependencies like torch-adjacent packages. The lesson from the httpx2 incident is that even lightweight HTTP clients must be explicitly pinned per-server. We updated our internal MCP server template (/opt/flipfactory/mcps/_template/pyproject.toml) on 2026-10-19 to include httpx2 >= 0.1.0 as a required dependency for any server that makes outbound HTTP calls — currently scraper, seo, leadgen, and competitive-intel.

The broader takeaway for the developer community: framework maintainers who make breaking dependency changes (even well-intentioned ones like switching to a better HTTP client) have an obligation to either maintain a compatibility shim or publish an explicit migration guide listing all known affected plugins. The LLM 0.33 changelog does note the httpx2 switch, but does not enumerate affected plugins. A machine-readable “breaking change manifest” would let plugin authors — and tools like uv — surface the issue automatically at install time.

Key takeaways

  • LLM 0.33 broke all plugins using httpx transitively — not just llm-tools-datasette 0.1.0.
  • llm-tools-datasette 0.1.1 (released 2026-10-18) fixes the issue with 1 explicit httpx2 dependency declaration.
  • FlipFactory’s scraper MCP server lost 3 days of valid data before our n8n anomaly monitor caught the silent failure.
  • PyPA’s own documentation requires every imported package to be a direct dependency — most plugin authors skip this.
  • Auditing llm plugins before any LLM core upgrade takes 10 minutes and prevents production data loss.

FAQ

Q: Do I need to update llm-tools-datasette if I’m still on LLM 0.32?

No. The httpx2 switch happened in LLM 0.33. If your LLM CLI is pinned to 0.32 or earlier, llm-tools-datasette 0.1.0 still works fine. Upgrade llm-tools-datasette to 0.1.1 only when you upgrade LLM to 0.33 or later — do both together to avoid the silent import failure.

Q: Will other LLM plugins break the same way after upgrading to LLM 0.33?

Yes, potentially. Any plugin that calls httpx without listing it as a direct dependency in its own pyproject.toml or setup.cfg is at risk. Audit your plugin list with llm plugins and check each repo’s dependency declarations before running pip install llm==0.33.

Q: Is httpx2 a drop-in replacement for httpx in my own code?

Mostly yes — the API surface is intentionally compatible for common use cases like httpx2.get(), httpx2.AsyncClient, and request/response objects. However, some advanced configuration options and transport-layer hooks differ. The pydantic/httpx2 GitHub repo maintains a migration guide; read it before doing a find-and-replace across a large codebase.

Further reading

  • flipfactory.it.com — production MCP server patterns, n8n workflow templates, and LLM plugin audit tooling we use across fintech and e-commerce clients.

About the author

Sergii Muliarchuk — founder of FlipFactory.it.com. Building production AI systems for fintech, e-commerce, and SaaS clients. We run 12+ MCP servers, n8n workflows, and FrontDeskPilot voice agents in production.

We have personally debugged silent plugin failures in live LLM environments — which means we write about dependency management from scar tissue, not speculation.

Frequently Asked Questions

Do I need to update llm-tools-datasette if I'm still on LLM 0.32?

No. The httpx2 switch happened in LLM 0.33. If your LLM CLI is pinned to 0.32 or earlier, llm-tools-datasette 0.1.0 still works fine. Upgrade llm-tools-datasette to 0.1.1 only when you upgrade LLM to 0.33 or later — do both together to avoid the silent import failure.

Will other LLM plugins break the same way after upgrading to LLM 0.33?

Yes, potentially. Any plugin that calls httpx without listing it as a direct dependency in its own pyproject.toml or setup.cfg is at risk. Audit your plugin list with `llm plugins` and check each repo's dependency declarations before running `pip install llm==0.33`.

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