I'm implementing a personal AI agent that is fully local inference with external memory that has access to my meetings, notes, Slack and Google Docs. Initially, it replaces Fireflies to capture notes from meetings and Slack.

Well I have a very specific use case. Me an my team made like this shared memory for LLMs: So an llm makes an mcp call to our api with a general question. An ai agent on our side determines which tools to call (search, graph exploration, etc) to find memory "fragments" based on tags and semantic search. and then the ai agent determines if the content of the "memory fragment" is relevant to the initial question and then it returns it.

No

I set up an MCP for jira, to hopefully avoid me from ever opening jira again.

i will just talk to the LLm, and ask it to set a task to in progress, tell me what to work on next, add tasks to sprints, tag tickets with labels / link them to epics etc

seems mildly helpful, with some slack mcp etc it could be useful for teams i think

i really don't want to just buy an agentic workflow from a website, so its important that i can just replace the model with whatever and that i have control of the mcp server