OpenHands / OpenHands/extensions

Add Memanto MCP integration to catalog

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Dominant language
Python
Stars
148
Forks
90
Avg merge
1d 17h
Merged PRs (30d)
36

Description

Problem or Use Case

Memanto provides persistent semantic memory for agents over MCP (remember, recall, answer, etc.), but it is not listed in OpenHands/extensions, so Agent Canvas cannot show an install card on /mcp like Tavily or Kagi.

Official MCP documentation (source of truth for server name, env vars, and tools):
https://docs.memanto.ai/integrations/mcp

Desired Behavior

Add a catalog entry aligned with other stdio API-key MCP integrations (e.g. Tavily, Kagi):

Regenerate integrations/catalog-index.js with npm run build:integrations.

This is an opt-in MCP backend; it does not replace OpenHands built-in file memory.

Acceptance Criteria
  • integrations/catalog/memanto.json validates against integrations/catalog.schema.json
  • npm run build:integrations succeeds
  • getIntegrationCatalogEntry("memanto") (JS) / get_integration_catalog_entry_model("memanto") (Python) returns the entry with stdio uvx + memanto-mcp and env fields from the Memanto MCP docs
  • Memanto appears in MCP-filtered catalog listings (listIntegrationCatalog({ mcp: true }) / list_integration_catalog_models(mcp=True))
References

Contributor guide

No contributing guide indexed for this repository

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Review integrations/catalog.schema.json and nearby stdio API-key entries, then inspect the catalog lookup entry points named in the acceptance criteria. Add the Memanto catalog data from the linked MCP documentation and run npm run build:integrations. Done means the generated integrations/catalog-index.js builds and both JavaScript and Python catalog lookups include the entry in MCP-filtered results.

Written by the indexing model from the issue text.

Assessment

Tech stack
javascript, python
Domain
api, tooling
Issue type
Feature
Difficulty
2/5
Estimated time
1-3 hours
Activity status
Active
Clarity
Clearly specified
Newbie friendliness
88/100

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