Alfresco – Page 2 – Open Source Integrated AI and Semantic Tech

Flexible GraphRAG v0.7.2 is out: Hyland Nuxeo data source, OAuth2 and ticket auth for Alfresco, OAuth2 for the MCP server

X.com Steve Reiner @stevereiner LinkedIn Steve Reiner LinkedIn Posts

Repost of my LinkedIn post from August 10, 2026 (original LinkedIn post)

Flexible GraphRAG v0.7.2 is out 🚀
🆕 Hyland Nuxeo is now a supported data source, with OAuth2, token, and basic authentication.
🔐 Hyland Alfresco data source gains OAuth2 and ticket authentication in addition to basic authentication.
🔑 The Flexible GraphRAG MCP Server optionally supports OAuth2 on the MCP transport itself.

📡 ActiveMQ carries Alfresco add, delete, and modify events, and Kafka carries Nuxeo document change events off the audit stream.

Alfresco and Nuxeo authentication works from the UI or through MCP, with or without the auto-sync incremental update system enabled, and on either the default pipeline or the Langflow visual ingest pipeline.

The python-alfresco-mcp-server was also updated, adding OAuth2 and ticket auth plus optional MCP transport OAuth2. Both projects build on the updated python-alfresco-api, which provides the enhanced OAuth2, ticket, and basic authentication.

Flexible GraphRAG is an Apache 2.0 open source AI context platform: a document processing pipeline (Docling, LlamaParse, or LiteParse), knowledge graph auto-building, ontologies and schemas, many LLM providers, GraphRAG and RAG, hybrid semantic search (fulltext, vector, property graph, RDF/SPARQL), AI query, and AI chat.

The backend is Python, with both LlamaIndex and LangChain fully supported. Angular, React, and Vue TypeScript frontends and an MCP server are included.

The stack supports 14 data sources (10 with incremental auto-sync), 15 property graph databases, 4 RDF triple stores, 10 vector databases, and OpenSearch / Elasticsearch / BM25 search, plus Alfresco and Nuxeo. All databases and dashboards can be enabled with the provided Docker Compose layout.

Optionally, the ingest pipeline, hybrid search, and AI query can run through customizable Langflow visual flows (12 custom components).

flexible-graphrag github: https://github.com/stevereiner/flexible-graphrag

python-alfresco-mcp-server github: https://github.com/stevereiner/python-alfresco-mcp-server

python-alfresco-api github: https://github.com/stevereiner/python-alfresco-api

Flexible GraphRAG now supports optional visual Langflow flows for ingest and search / AI query, plus configurable Flexible Langflow components

Flexible GraphRAG on GitHub

X.com Steve Reiner @stevereiner LinkedIn Steve Reiner LinkedIn Posts

Repost of my LinkedIn post from July 6, 2026 (original LinkedIn post)

The Flexible GraphRAG app now supports optional visual Langflow flows to customize the ingest pipeline and search / ai-query flows used “under the covers” of the UI (OpenRAG like). Also have configurable “Flexible” Langflow components to use in agentic apps or for RAG / GraphRAG. These include data source (13 sources ), document processor (Docling / LlamaParse), text splitter/chunking, KG extraction supporting ontologies for both pg and rdf dbs, vector (10 dbs), search (3 dbs), property graph (15 dbs). rdf graph (4 dbs), hybrid search, ai query / chat
Github: https://github.com/stevereiner/flexible-graphrag

Update: works with the incremental auto update sync

From my follow-up LinkedIn post from July 8, 2026 (original LinkedIn post)

I forgot to mention that the Flexible GraphRAG incremental auto update sync system works with the customizable visual ingestion pipeline flow (if ENABLE_LANGFLOW_FLOWS is configured). The flow is used for initial ingests, adds, and updates. The Langflow components are Python based and use the Flexible GraphRAG Python "framework“. Auto update sync with the Hyland Alfresco data source is tested and works with the ingest flow. These should work too: S3, Google Drive, OneDrive, SharePoint, Box, and Local Filesystem. For GCS and Azure Blob Storage, I have a fix coming soon. Postgres is used to manage the update system. Github: https://github.com/stevereiner/flexible-graphrag

Big News: Flexible GraphRAG now supports Incremental Update Auto Sync from Data Sources

Flexible GraphRAG on GitHub

X.com Steve Reiner @stevereiner LinkedIn Steve Reiner LinkedIn Posts

Repost of my LinkedIn post from February 6, 2026 (original LinkedIn post)

Big News: Flexible GraphRAG now supports Incremental Update Auto Sync from Data Sources
Huge New Feature: Flexible GraphRAG check-in: Added Incremental Update Auto Sync from 9 data sources to all supported vector, search, and graph databases. Added Postgres state management.
🌟 Github: https://github.com/stevereiner/flexible-graphrag

• All auto syncing data sources working: S3 (SQS events), Hyland Alfresco (ActiveMQ events), Azure Blob, GCS (Pub/Sub), Google Drive, Box, OneDrive, SharePoint, Filesystem (watchdog).

• All 10 vector databases working with this (Qdrant, LanceDB, Elastic, OpenSearch Project, Chroma, Milvus, created by Zilliz, Weaviate, Pinecone, PostgreSQL pgvector, Neo4j)

• All 3 full text search engines working with this (Elasticsearch, OpenSearch, built-in LlamaIndex BM25)

• Graph databases working with this: Neo4j, FalkorDB, ArcadeDB (fix to delete coming), MemGraph. More testing needed with Kuzu, NebulaGraph, Amazon Neptunes.

Flexible GraphRAG or Flexible RAG, an Apache 2.0 open source Python platform, uses LlamaIndex , supports 8 graph databases, 10 vector databases, 3 search engines, and 13 data sources (9 auto-sync) Also supports knowledge graph auto-building, schemas, 9 LlamaIndex LLMs, Docling or LlamaParse doc processing, GraphRAG mode, RAG only mode, Hybrid search, AI query, AI chat. Has React, Vue, and Angular TypeScript frontends, a FastAPI backend, and a REST API. Also has a FastMCP MCP server. Has a convenient docker compose that can include any of the databases (Vector, Graph, Search, Alfresco) and Dashboards / Consoles.
Blog: https://integratedsemantics.org/
X.com: https://x.com/stevereiner

Flexible GraphRAG: Observability support, SharePoint and OneDrive data sources working, 9 LLM providers, “Skip graph” checkbox

Flexible GraphRAG on GitHub

X.com Steve Reiner @stevereiner LinkedIn Steve Reiner LinkedIn Posts

Repost of my LinkedIn post from January 5, 2026 (original LinkedIn post)

Shown: updated Flexible GraphRAG with Neo4j, Observability with Grafana Labs , GitHub 🌟 https://github.com/stevereiner/flexible-graphrag , updates:
1. Observability support added with OpenTelemetry, Prometheus, Grafana, Jaeger, and OpenLIT
2. SharePoint and OneDrive data sources fixed and now working (13 data sources: filesystem, Alfresco, SharePoint, Box, CMIS, S3, GCS, Azure Blob, OneDrive, Google Drive, web sources)
3. Added LLM Providers (now 9 total) : OpenAI, Azure OpenAI, Google Gemini, Vertex AI, Anthropic Claude, Amazon Bedrock, Ollama, Grog, Fireworks AI, and Ollama. Uses LlamaIndex.
4. Embedding providers can be used independently..
5. Like KG Spaces (Github 🌟 https://github.com/stevereiner/kg-spaces-aca) for Hyland Alfresco ACA, added a “Skip graph” checkbox for per ingest control. Skip graph allows on each ingest to have fast RAG ingest speed (vector+full-text) or a full GraphRAG ingest (vector+full-text+graph). Hybrid search and AI query / AI chat works with all that is available from mixed kinds of ingests.
6. Flexible GraphRAG MCP server: added support for all 13 data sources, per ingest skip_graph option , data source config options, full REST API parity.
7. Backend REST API (also supports all 13 data sources), added support for per ingest skip graph, also for KG Spaces: multi-file ingest NodeDetails list with nodeids, get by path for regular Flexible GraphRAG with updated Python Alfresco API package (Github 🌟https://github.com/stevereiner/python-alfresco-api)
8. Added Python backend pyproject.toml, llama-core (no llama-index) and integrations only, to avoid package version issues.

Flexible GraphRAG or Flexible RAG, an Apache 2.0 open source Python platform, uses LlamaIndex , supports 8 graph databases, 10 vector databases, 3 search engines, and 13 data sources, Also supports knowledge graph auto-building, schemas, 9 LlamaIndex LLMs, Docling or LlamaParse doc processing, GraphRAG mode, RAG only mode, Hybrid search, AI query, AI chat. Has React, Vue, and Angular frontends, and a FastAPI backend. Also has a FastMCP MCP server. Has a convenient docker compose that can include any of the databases (Vector, Graph, Search, Alfresco) and Dashboards / Consoles.

X.com Post on updates
https://x.com/stevereiner/status/2007534742908846552
Integrated Semantics Blog:
https://integratedsemantics.org/

Initial check-in of KG Spaces: Flexible GraphRAG integration with the Hyland Alfresco ACA client

Flexible GraphRAG on GitHub

X.com Steve Reiner @stevereiner LinkedIn Steve Reiner LinkedIn Posts

Repost of my LinkedIn post from December 18, 2025 (original LinkedIn post)

Initial checkin of KG Spaces integration of Flexible GraphRAG with Hyland Alfresco ACA client available now. Please 🌟 Star both github repos:
kg-spaces-aca https://github.com/stevereiner/kg-spaces-aca and
flexible-graphrag https://github.com/stevereiner/flexible-graphrag

Multi select files / folders in regular ACA UI, in process tab can optionally choose skip graph ( search + vector only). Hybrid search tab (with hybrid search or AI query), and AI chat tab (Search is OpenSearch Project or Elastic, vector is one of 10 vector databases, graph is one of 8 graph databases including Neo4j, ArcadeDB, FalkorDB).

Flexible GraphRAG or Flexible RAG, an Apache 2.0 open source python platform, uses LlamaIndex , supports 8 graph databases, 10 vector databases, 3 search engines, and 13 data sources, Also supports knowledge graph auto-building, schemas, LlamaIndex LLMs, Docling and LlamaParse doc processing, GraphRAG mode, RAG only mode, Hybrid search, and AI query / chat. Has React, Vue, and Angular frontends, and a FastAPI backend. React, Vue, Angular, Also has a FastMCP MCP server.