面试题库

分析过程 · 先想清楚再作答

1. 题眼在后半句。只会说「MCP 更标准更解耦」的人，等于说「微服务更解耦」——听起来对，但没有判据，面试官会立刻追问「那你们所有工具都做成 MCP server 了吗」。
2. 先给判据，而且要是可执行的三条：能力要被多个宿主复用、能力由另一个团队或第三方维护、需要不改宿主代码就能增删能力。命中任意一条才考虑，**一条都不命中就直接写本地函数**——把默认答案摆成「不上」，这条比三条判据本身更能体现工程判断。
3. 每条判据配一句为什么：多宿主复用把 N 乘 M 变成 N 加 M；别人维护时进程边界就是责任边界，他们改他们的、你不用发版；热插拔让加一个内部工具从一次发布降级成一次配置变更。
4. 然后老实说代价，这是区分「用过」和「读过」的地方：多一个进程要保活、多一次握手要处理超时与重连、排障链路从一段变三段——工具没被调用，现在可能是模型没选、可能是 schema 翻译时丢了字段、也可能是 server 压根没起来。stdio 的子进程还要你自己回收，否则留孤儿进程。
5. 还有一条容易被忽略但很加分：MCP 不改变你的成本结构。工具描述照样每轮都进上下文，工具多了照样会让模型选错——D5 那条「工具超过一定数量就该合并描述」在接了 MCP 之后一字不变，甚至更需要，因为现在别人可以往你的工具列表里塞东西。
6. 可以预期的追问：那内部工具一律不上 MCP 吗？不是。有一类值得例外——你希望它能被 IDE 里的助手和运维机器人一起用，那第一条判据就命中了，即使它是你自己维护的。

How to reason about it · think before answering

1. The hinge is the second half. Answering only 'MCP is more standard and decoupled' is like saying 'microservices are more decoupled' — true-sounding but with no criterion, and the interviewer will immediately ask whether you turned every tool into an MCP server.
2. Give three actionable criteria: the capability must be reused by more than one host, owned by another team or a third party, or added and removed without changing host code. Any one of them justifies MCP; none of them means write a local function. Making 'no' the default answer shows more engineering judgment than the criteria themselves.
3. Attach a reason to each: multi-host reuse turns N times M into N plus M; external ownership makes the process boundary the responsibility boundary, so their change is not your release; hot-swapping demotes adding an internal tool from a deployment to a config change.
4. Then state the costs honestly, which is where shipped experience shows: another process to keep alive, another handshake with its own timeouts and reconnects, and a debugging path that went from one hop to three — a tool that never got called might mean the model did not pick it, the schema lost fields in translation, or the server never started. On stdio you also own reaping the child process.
5. One more point that is easy to miss and scores well: MCP does not change your cost structure. Tool descriptions still enter the context every turn, and more tools still degrade tool selection. The rule that you should consolidate tools past a certain count survives MCP unchanged — arguably it matters more, because now other people can add entries to your tool list.
6. Expect the follow-up: so internal tools never go through MCP? Not quite. If you want the same capability available to an IDE assistant and an ops bot as well, the first criterion is met even though you own the code.

分析过程 · 先想清楚再作答

1. 这题考的是工程判断，不是技术偏好。开口就说「专用向量库更专业」的人会被追问到答不上来；面试官想看的是你有没有把迁移成本算进去。
2. 先给默认立场并给出理由：第一版留在 PostgreSQL，因为事务、备份、时间点恢复、权限、跟业务表 JOIN 和现成的运维工具全是白送的。多一个数据库就多一份同步、一份一致性问题、一份值班负担，这些成本很少被写进选型文档。
3. 然后给四条可量化的触发线：数据量（判据不是行数而是索引还塞不塞得进内存）、写入频率（分钟级流式更新会让聚类失真、让图持续膨胀）、过滤复杂度（十几个属性的任意组合让部分索引和分区都排列组合不过来）、团队运维能力（没人愿意长期照看第二个数据库，前三条再成立也别搬）。
4. 第三条要展开一点，因为它最常是真正的原因：专用向量库把过滤做进了索引结构本身，而不是扫完索引再筛，所以在复杂过滤下天然占优。把这一点说出来，说明你理解的是机制而不是口碑。
5. 还要主动给一条常被忽略的替代路径：很多「向量检索不够用」的问题，真正的解法是混合检索加重排，而不是换数据库。先把关键词一路加回来、把重排接上，再决定要不要搬——顺序搞反了会白搬一次。
6. 可预期的追问：真要搬怎么迁？答分三步——先双写并在影子流量上比对两边的召回与延迟，再把读流量按比例切过去，最后才停掉旧路径。中间任何一步指标不达标就停下，这比一次性切换安全得多。

How to reason about it · think before answering

1. This tests engineering judgement, not tooling preference. Opening with 'dedicated vector databases are better' invites follow-ups you cannot answer.
2. State the default position and justify it: keep the first version in PostgreSQL, because transactions, backups, point-in-time recovery, permissions, joins with business tables and the tooling your team already knows all come free. A second datastore adds synchronisation, a consistency surface and an on-call burden that selection documents rarely price in.
3. Then give four measurable triggers: data volume (the test is whether the index still fits in memory, not the raw row count), write frequency (minute-level streaming updates distort clusters and inflate graphs), filter complexity (arbitrary combinations of a dozen attributes defeat both partial indexes and partitioning), and operational capacity.
4. Expand on filter complexity, because it is most often the real reason: dedicated vector databases push filtering into the index structure instead of applying it after the scan, which is a mechanical advantage rather than a reputational one.
5. Volunteer the alternative people skip: many 'vector search is not good enough' problems are actually solved by hybrid retrieval plus re-ranking, not by a new database. Add the keyword path and a re-ranker first, then decide.
6. Expected follow-up: how would you migrate? Dual-write, compare recall and latency on shadow traffic, shift read traffic gradually, and only then retire the old path. Stop at any step where the metrics regress.