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spranab

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1 points·by spranab·4 months ago·0 comments

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1 points·by spranab·5 months ago·0 comments

Show HN: Brainstorm-MCP – Let GPT, DeepSeek, and Groq Brainstorm Together

github.com
2 points·by spranab·5 months ago·1 comments

Show HN: Saga – SQLite project tracker for AI coding agents

github.com
4 points·by spranab·5 months ago·2 comments

Show HN: Saga – A Jira-like project tracker MCP server for AI agents (SQLite)

4 points·by spranab·5 months ago·5 comments

What happens when you put Claude, GPT, Grok, and DeepSeek in the same room?

warpmode.io
1 points·by spranab·5 months ago·1 comments

Show HN: SDF Protocol – Pre-compiled semantic JSON for AI agent web consumption

sdfprotocol.org
1 points·by spranab·5 months ago·6 comments

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·5 months ago·discuss
Thanks for the excellent references! We actually just added a SKILL.md following the agentskills.io spec based on your suggestion — it's live now: https://github.com/spranab/saga-mcp/blob/master/.skills/saga...

Great point about sqlite-utils FTS. Saga already has full-text search via tracker_search across all entities (projects, epics, tasks, notes), but we're using basic LIKE queries — proper SQLite FTS5 indexes would be a meaningful upgrade for larger projects. Adding it to the roadmap.

The bugwarrior/syncall direction is interesting too. A github_sync tool that pulls issues into Saga's local tracker (and optionally pushes status back) would close the loop between local agent planning and team-visible issue trackers. Definitely something worth exploring.

Re: SWE-bench agents and issue tracking — most SWE-bench agents read the issue description as input but don't write back to GitHub. Having a local structured tracker that an agent can read/write freely (without API rate limits or auth concerns) is exactly the gap Saga fills.
spranab
·5 months ago·discuss
I built an MCP server that lets Claude (or any MCP client) orchestrate structured debates between multiple LLMs.

You give it a topic, it sends it to all configured models in parallel, they see each other's responses, refine their positions over multiple rounds, and a synthesizer produces a final consolidated output.

Works with OpenAI, DeepSeek, Groq, Ollama, Mistral, Together — anything with an OpenAI-compatible API.

npx brainstorm-mcp
spranab
·5 months ago·discuss
Thanks for your valuable feedbacks.

SQLite handles this well in practice. saga-mcp uses WAL mode with busy_timeout=5000 and synchronous=NORMAL, so concurrent writes queue up rather than fail. The intended use case is one agent per project per session — if you had multiple agents writing to the same .tracker.db, WAL mode serializes the writes transparently.

For MCP adoption — it's growing fast. Claude Code, Claude Desktop, Cursor, and Windsurf all support it natively now. The spec is simple (JSON-RPC over stdio or SSE), so the barrier to both building and consuming MCP servers is low.
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·5 months ago·discuss
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·5 months ago·discuss
That actually is great, we can add ads detection and extract only the relevant information. Thanks @ksaj
spranab
·5 months ago·discuss
What do you mean? I just wanted to share something I am working on. Trying to understand what you meant by ads.