Summary
Wraps the Alembica structured extraction library as an MCP server, giving you tools to validate extraction schemas, estimate token costs across different LLM providers, run semantic extraction jobs on unstructured text, and query available schemas. Built for research workflows where you need to transform documents, articles, or corpora into structured datasets using OpenAI, Anthropic, Google, Cohere, DeepSeek, or self-hosted models. The cost estimation tool is handy for budgeting before running large extraction jobs, though it only works with public API providers. Runs via stdio transport from the Go binary or GHCR container. Reach for this when you're building data pipelines that need repeatable LLM extraction with cost visibility.
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alembica
Open Science Software for Semantic Synthesis and Extraction of Information from Unstructured Sources.
About
alembica simplifies the use of Large Language Models (LLMs) to extract structured datasets from unstructured corpora of text.
It provides a flexible and scalable framework to process, synthesize, and transform textual information into structured formats suitable for analysis and further processing.
Supports OpenAI, Google AI, Anthropic, Cohere, DeepSeek, Perplexity, AWS Bedrock, Azure AI, Vertex AI, and Self-Hosted OpenAI-compatible providers.
Installation (Go)
To install alembica in Go, run:
go get github.com/open-and-sustainable/alembica
If you want to use alembica in other programming languages, check out the C-Shared Library in the User Guide.
Documentation
User Guide – Learn how to use alembica in different programming languages.
API Reference – Explore the Go package documentation.
MCP Server
alembica includes an optional MCP server for agent tool access.
The MCP server can be used from a locally built Go binary, the GHCR container image, or the MCP Registry.
Available in the official MCP Registry:
- https://registry.modelcontextprotocol.io/?q=alembica
- Server ID:
io.github.open-and-sustainable/alembica-mcp
See the User Guide MCP page for installation options, run commands, and tool schemas.
MCP Registry publishing
The MCP server is published to the MCP Registry by GitHub Actions when a version tag such as v1.2.3 is pushed.
The workflow uses GitHub OIDC for authentication, and each new registry version is published explicitly by CI rather than implicitly from GitHub Releases.
Features
- Validation of Input – Ensures that queries are correctly formatted to support proper interaction with models.
- Cost Assessment – Calculates token costs based on the requested extraction and different model pricing.
- Data Extraction – Processes unstructured text and transforms it into structured datasets for further analysis.
Note: Cost estimation is not supported for Self-Hosted, AWS Bedrock, Azure AI, or Vertex AI providers and will return zero.
Optional model fields for cloud/local providers:
base_urlandapi_versionfor Azure/OpenAI-compatible endpointsregionfor AWS Bedrockproject_idandlocationfor Vertex AI
Use schemaVersion: "v2" when you need these cloud/local provider fields or non-enumerated model IDs.
Authors & Contributions
Author: Riccardo Boero - ribo@nilu.no
Contributions are welcome!
License
alembica is licensed under the GNU AFFERO GENERAL PUBLIC LICENSE, Version 3.
Citation
Boero, R. (2025).
alembica- Open Science Software for Semantic Synthesis and Extraction of Information from Unstructured Sources. Zenodo. https://doi.org/10.5281/zenodo.14899666
Featured
Keep your Mac awake while Claude Code and 40+ AI agents run. Sleeps when they're idle.
One time payment $9 →Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
Start earning →Registryactive
Packageghcr.io/open-and-sustainable/alembica-mcp:0.3.3
TransportSTDIO
UpdatedApr 23, 2026