Tahsine Kajola SALAMI

Corpus Hub contributor since 2026-10-19

Tahsine Kajola SALAMI's work was selected for the XERJ Corpus Hub, the open reference memory AI coding agents search before they write code. When an agent meets the same problem, it gets this implementation back as a worked example, with the author and the repository attached.

1corpus

1selected commit

5files

272lines

★ 1GitHub stars on repo

Totals across every corpus @Tahsine appears in; a commit selected for two corpora counts once. Files and lines count the selected commits; each corpus indexes the whole repository at its pinned commit.

What an agent can do with the momo-mcp corpus

Tahsine/momo-mcp: Serveur MCP pour Mobile Money en Afrique de l'Ouest francophone (MTN MoMo, Moov Africa, Orange Money): paiements, statuts et transferts…

Look up how momo-mcp implements africa, ai-agents, fintech, with answers cited to file and line.
Reuse a worked example: the commit “Renforce la securite (audit Bryand): annotations, plafonds, allowlist…” (5 files · Python).
Answer from momo-mcp's real Python source instead of memory (AI, prompts and agents).

Example questions

How does momo-mcp implement africa?
What does src/momo_mcp do in momo-mcp?

Paste it into your AI agent. It clones the repo at the pinned commit and indexes it on your machine.

Search the GitHub repository Tahsine/momo-mcp with XERJ (https://hub.xerj.org/corpus/tahsine--momo-mcp).
Run these in a shell, in order, and check each result before the next:
1. xerj --help  (success: it prints usage). If xerj is missing: curl -fsSL https://xerj.org/get | sh
2. git clone https://github.com/Tahsine/momo-mcp momo-mcp && git -C momo-mcp checkout f6e95f4a18eedb32814eb1b833837300f15ef4a1
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./momo-mcp --url http://127.0.0.1:9200 --prefix momo-mcp --progress plain
5. xerj autoindex map --url http://127.0.0.1:9200
Then answer my question from the indexed files and cite the ax_path of every hit. Query syntax: https://xerj.org/llms.txt
Licence: MIT. Keep the copyright notice and credit the authors.

corpus tahsine--momo-mcp · AI, prompts and agents
Related corpora: fastmcp, atoma-run--atoma, hussainn7/plip-oss, elbayoumi/crewloom
AI search and retrieval with XERJ · Case study: reference coding for agents

Selected work

GitHub ★ 1

Tahsine/momo-mcp

f6e95f4a18 Renforce la securite (audit Bryand): annotations, plafonds, allowlist…

selected commit: 5 files · 272 lines · Python · src/momo_mcp, tests, the project root

The corpus is the whole repository at the pinned commit, not only the files of the selected commit.

selected · in licence reviewcorpus tahsine--momo-mcpAIMITafricaai-agentsfintechmcpmobile-moneymodel-context-protocol agreed 2026-10-19

Not installable yet: this corpus is not in the hub registry until its licence review passes, so xerj corpus add and xerj ask cannot fetch it. It becomes installable when this card says live in the hub.

[![XERJ Corpus Hub contributor](https://hub.xerj.org/contributors/Tahsine/badge.svg)](https://hub.xerj.org/contributors/Tahsine)

Included with the author's permission (email, 2026-10-19), under each repository's own licence, with attribution. Want it removed? Reply to the email or open an issue on xerj-org/xerj.