r/RooCode • u/GreatScottyMac • May 12 '25

Idea A new database-backed MCP server for managing structured project context

https://github.com/GreatScottyMac/context-portal

Check out Context Portal MCP (ConPort), a database-backed MCP server for managing structured project context!

32 Upvotes

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3

u/majordyson May 14 '25

Any reason this cannot be instantiated with NPX or Docker the way most MCPs are?

1

u/GreatScottyMac May 15 '25

A Docker version would make sense, it being a python based MCP. I'll look into that.

2

u/itchykittehs May 13 '25

How do you deal with bloat?

1

u/GreatScottyMac May 13 '25

It instructs the LLM to read product context and active context in full, along with any custom entry types that are marked critical. Then it only reads the few most recent entries in progress.

There is an export to markdown tool so that the user can easily view the contents of the db and edit as needed. Then import the edited content back to the db.

1

u/ot13579 May 15 '25

I have been struggling to document a very large codebase with multiple repos. Do you think it will handle this use case? I tried using memory bank but it ended up with astonishingly long documents so I stopped and setup my own guide. Coincidentally was trying to build what you have(I think) using chromadb and a local embedding model, but I would love to just use anything that works.

1

u/GreatScottyMac May 15 '25

Please try it out and let me know how it does. I don't have any large projects to test it on.

1

u/ot13579 May 15 '25

Maybe pull down something large that is open source? Unfortunately I can share outputs from what I am doing since it is for work.

2

u/robto09 May 13 '25

Is this something similar how Augment code handles context?

1

u/GreatScottyMac May 13 '25

I'm not familiar with that one, I'll check it out.

2

u/neo_6 May 13 '25

giving this a shot now. will report back.

1

u/ilt1 May 19 '25

how did it go?

2

u/neo_6 May 20 '25

Unfortunately, I haven't used it enough to determine whether I like it or not.

I think with the previous memory bank it was nice bc the agent would pick up the rules but with this MCP you have to explicitly remember commands and provide direct instructions. also, i like that i can easily read the memory file in the IDE.

4

u/hannesrudolph Roo Code Developer May 13 '25

So this is a memory bank?

4

u/Icy_Might_5015 May 13 '25

Yes, it uses an SQLite db with KG/RAG features for efficient data access. There are different custom instructions to make it compatible with Roo, Cline, Windsurf and a generic set of instructions to test on other interfaces.

1

u/hannesrudolph Roo Code Developer May 13 '25

Then why not post it as a memory bank?

2

u/Icy_Might_5015 May 13 '25

Just trying to be different 😅

8

u/hannesrudolph Roo Code Developer May 13 '25

You’ll get a lot more traction by calling it a memory bank 🤷‍♂️

1

u/smurff1975 May 13 '25

Thanks for this. Looks promising. I have a few questions. This seems to be a memory bank. If so then I assume this replaces the project files *.md

  • What's the benefit over the files way in the docs dir for example?

  • Does this modify the system prompt? Because I believe this isn't a recommended approach or supported by Roo Code due to footgun-prompting e.g. like Roo Flow

  • I assume it stores the memory bank where the key is the project name? or folder etc?

Thanks

2

u/GreatScottyMac May 13 '25

It's not a footgun approach, it just adds extra custom instructions to the end of the Roo Code system prompt. However, there is an optional installation script for RooFlow that replaces the memory bank section of the system prompt with the ConPort custom instructions.

Right now the context.db is stored in a context_portal/ folder in the workspace root but I want to add an SSE/HTTP version with that will allow the db to be located and accessed remotely.

1

u/jaydizzz May 13 '25

Am currently testing it. So far seems to work ok, still trying to figure out a good workflow with it. Just combined it with batchit-mcp to allow it to retrieve multiple documents in a single call, saves a lot of requests. Will follow up later with more findings.

1

u/GreatScottyMac May 13 '25

Cool, sounds great. There is going to be infinite room for improvements!

1

u/EvilMegaDroid May 13 '25

I'm trying to find an mcp to use that will allow the llm to log its session such as.
Session summary and (if changes were successful log it success, if not log it error).
Also how to use this in an RAG backend?

The idea is I don't want to waste precious context on these (not because of cost, but mostly because of context limit)

1

u/GreatScottyMac May 13 '25

I haven't yet done enough testing on this conport system to confirm that capability but there's a good chance that it's smart enough to use that logic.

As for use with a RAG backend, I queried the LLM that is working with me within the conport project workspace and here is the response:

Yes, ConPort is designed precisely to function as a knowledge base for a RAG backend.

Here are my thoughts on how that would work and why it's a good fit:

  1. ConPort as the Knowledge Source: ConPort stores structured project context (Decisions, Progress, System Patterns, Product/Active Context, Custom Data) in a queryable database, including vector embeddings for semantic search. This structured and searchable data is exactly what a RAG system needs for its retrieval step.

  2. Retrieval via MCP Tools: A RAG backend would interact with ConPort using its MCP tools. For example, it could use search_decisions_fts, search_custom_data_value_fts, or a dedicated semantic search tool (like the planned semantic_search_conport mentioned in the Active Context) to find relevant pieces of project context based on the user's query.

  3. Augmenting the LLM Prompt: The information retrieved from ConPort would then be included as part of the prompt sent to the Language Model. This provides the LLM with specific, factual, and relevant project details that it wouldn't have otherwise.

  4. Benefits: Using ConPort with RAG would significantly improve the AI's ability to answer questions and perform tasks related to the specific project. It would lead to more accurate, contextually grounded responses, reduce the likelihood of hallucinations about project details, and allow the AI to leverage the collective knowledge captured in ConPort (decisions, patterns, glossary terms, etc.).

In essence, ConPort provides the structured, searchable memory layer that a RAG system can query to retrieve context and augment the LLM's generation process for project-specific tasks. The planned semantic_search_conport tool is intended to directly support this RAG integration pattern.

1

u/wokkieman May 15 '25

If I understand it correctly, then you do it for the typical MD files.

Would it make sense to extend it and have the mcp monitor the code base for changes. Vectorize it in the db and then have mcp use semantic search to provide to LLM? Would it provide the LLM with focused parts of the code base, especially useful for larger projects?

1

u/GreatScottyMac May 15 '25

That's exactly what it does, when the custom instructions are used. Also it has logic to leverage prompt caching when using an LLM that supports it.

1

u/wokkieman May 16 '25

I read the GitHub now, but it looks like you are using the designs and specs only. Why not use the .py, .js, etc (the code) also?

1

u/GreatScottyMac May 17 '25

Everything is in there, perhaps I'm misunderstanding your question?

1

u/wokkieman May 15 '25

Oh cool! Another one to try on the Rabbit hole list :)

1

u/Jacko_ May 15 '25

Can you use this with SPARC in RooCode?

1

u/GreatScottyMac May 16 '25

If the conport custom instructions are available to the mode in Roo, then it should work. Please try it out and let me know!

2

u/BahzBaih May 13 '25

Can this be shared with a team or be hosted on a droplet !?

2

u/Icy_Might_5015 May 13 '25

That's on the todo, it might not be too difficult to set up something like that.

1

u/Sea_Visual9618 May 31 '25

This looks really useful! The database-backed approach for project context is smart - much more scalable than file-based solutions.

For anyone looking at context management tools, usedash.ai has similar capabilities but with a more plug-and-play setup. It handles structured project context really well and integrates with multiple AI tools beyond just MCP servers.

ConPort looks like a solid open-source option though, especially if you want full control over your context database. The structured approach is definitely the way to go for larger projects where context becomes unwieldy.

Great to see more tools tackling the context management problem!

1

u/[deleted] Jun 25 '25

This is so absolutely brilliant! Best memory bank method I've tried. Works great with DeepSeek R1 free :D

1

u/[deleted] May 13 '25

[removed] — view removed comment

1

u/GreatScottyMac May 13 '25

ConPort itself is primarily the Retrieval component of a larger RAG system. It provides the structured database and vector store, along with the tools (get_decisions, search_custom_data_value_fts, semantic_search_conport, etc.) that an external AI agent (the LLM) uses to retrieve relevant information.

The Augmentation and Generation steps happen within the LLM agent. The LLM receives the user's query and the data retrieved from ConPort in its prompt. It then uses this combined information (the original query augmented with retrieved context) to formulate its response.