mcpgov
A production-grade MCP server over Postgres, providing secure data operations with tenant isolation, exact-once mutations, loop-aware rate limiting, and a tamper-evident audit trail.
README
mcpgov
A production-grade MCP server over Postgres, where the hard 20% is the point: authentication, tenant isolation, provably idempotent mutations, loop-aware rate limiting, and a tamper-evident audit trail — each claim pinned by a test that runs against a real database, and an end-to-end adversarial demo that attacks the live server over real HTTP in CI.
Why
Every company is wrapping internal systems in MCP servers so agents can use them. Most wrappers are demos: the tools work, and nothing stops a retried mutation from applying twice, a token from reading another tenant's rows, or an agent loop from hammering the same failing call all night. This repo is the missing 80-to-100 stretch, built as five controls that a tool author cannot forget, because they live in the middleware chain and the database rather than in tool bodies.
The controls, and the evidence for each
1. Identity is verified, not asserted. OAuth-style short-lived Bearer
tokens (HS256, exp/aud/iss/jti all required), plus RFC 7523 jwt-bearer
federation: an IdP-issued assertion is exchanged for a local token after
signature-by-kid, audience, issuer, expiry-with-bounded-skew, and single-use
jti checks. Group-to-team mapping is a declarative allowlist; an unmapped
group grants nothing, including a group that happens to be named after a real
team. 19 tests, including forged signatures, alg=none, replayed assertions,
and cross-audience confusion.
2. Tenant isolation is enforced by the database, not the queries. Postgres
row-level security with FORCE, keyed on a GUC populated only from verified
token claims — there is no request field through which a client names a tenant.
The server runs as a role that is neither owner nor superuser (either would
bypass RLS silently; a test asserts this about the running role). Teams are
jsonb, not CSV, after measuring that CSV encoding let a principal entitled to
gamma,delta read the distinct team literally named gamma,delta. Cross-tenant
reads return not_found byte-identical to genuinely absent ids.
3. Mutations are exactly-once under retry storms. A claim-then-execute
ledger: the idempotency claim and the business write commit in one transaction,
duplicates replay the stored response marked _replayed, a key reused with
different arguments is refused, and only non-retryable failures are cached
(caching a transient one would convert a blip into a permanent failure that
looks healthy). Pinned by a 16-thread concurrent-duplicates test repeated 5
times, plus crash-recovery: an unclean death does not poison the key.
4. Rate limiting distinguishes a runaway loop from a legitimate burst. Two
layers, because "too fast" and "stuck" are different problems: a GCRA shaper
per (principal, tool_class) that delays, and a loop breaker that looks for
repetition without progress and opens a per-tool circuit. On the seeded
evaluation (200 trials/family, reproduced in CI byte-for-byte):
| workload | outcome |
|---|---|
| 5 runaway families (same-error, cycle, no-op write, infinite transient retry, idempotent replay) | broken in 100% of trials, median 8 wasted calls |
| 6 legitimate families (poll, paginate, fan-out, backoff retry, burst, small worklist) | 0 false breaks |
| declared long poll | bounded by its declared budget, by design |
| undeclared poll | known false positive, documented — without a declaration it is indistinguishable from a no-progress loop |
| token-bucket baseline | denies 41/80 of the runaway and 41/80 of the legitimate burst at identical arrival rates — its verdict is a function of rate, the label is a function of shape; it never breaks a loop, only slows it |
5. The audit trail is tamper-evident, including truncation. Every attempt —
allowed, denied, unauthenticated — is one row in an HMAC hash chain, with
arguments redacted to digests. The chain head lives in a singleton row read
under FOR UPDATE (the naive ORDER BY seq DESC LIMIT 1 head forked under
concurrency: 16 concurrent appends produced 9 distinct predecessors, and
verification cried tamper on clean traffic). Verification requires a separate
auditor login the server never holds, because the writer being unable to read
the whole log — and the reader being unable to write — is what makes "the chain
verified" a statement about the data rather than the writer's self-report.
Deleting the tail is detected too, which hash-chaining alone cannot see.
The demo: the live server, attacked over real HTTP
demos/session.py boots mcpgov serve, mints tokens with the CLI, and drives
13 acts through the official MCP client — no token (401 with the RFC 9728
challenge), forged signature, scope escalation, a retry storm of duplicated
mutations, key reuse with different arguments, cross-tenant probing, a runaway
loop broken on attempt 7 while other tools keep answering, tenant-scoped audit
reads, chain verification, and a superuser rewriting one row's deny to
allow — caught with the exact seq. Each act asserts its expected outcome; CI
fails if any deviates. Transcript: results/demo-session.json.
To point Claude Code or Cursor at it interactively: docs/clients.md.
Run it
Needs Python 3.12+, uv, and any Postgres 14+.
uv sync
# the full suite: 100 tests, most against the real database
MCPGOV_TEST_DSN='postgresql://postgres@127.0.0.1:5432/postgres' uv run pytest
# the adversarial demo (creates its own scratch database)
MCPGOV_DEMO_DSN='postgresql://postgres@127.0.0.1:5432/mcpgov_demo' \
uv run python demos/session.py
# the limiter evaluation (seeded; CI diffs the output against the committed file)
uv run python scripts/eval_limiter.py
Design notes worth stealing
- Controls in middleware, not tool bodies. A check inside a tool is a check a new tool can forget, silently. The guard wraps every inbound message, so it also sees calls to tools that do not exist and calls that fail schema validation — attempts worth auditing that a per-tool check never sees.
- Middleware sees the wire format.
call_nextreturns a JSON-RPC dict (isError, camelCase), not the typedCallToolResult. The attribute spelling returned its default forever: every refusal was audited asallow, and loop detection was structurally dead in the live server while the offline harness scored it at full recall. The tests now drive a real client session. INSERT ... RETURNINGre-evaluates the SELECT policy on the new row — so the unscoped audit appender could not record tenant-tagged events at all.- Permissive RLS policies apply by role membership, not the active role. Granting the app role membership of the auditor role (the convenient wiring) switched the full-read policy on for every app query and removed the tenant boundary from audit reads without a single error.
- Retryability is declared once, per error code, and consulted by both the idempotency cache and the loop breaker's thresholds — a permanent failure misfiled as transient would let a runaway run 20 calls instead of 6.
Limitations, honestly
- The IdP in the federation tests is a local fixture with published keys, not a live Okta/Entra tenant; the validation logic is real, the network hop is not.
LocalTokenVerifieris symmetric-key (HS256) — right for a single-server deployment, not for a fleet where issuers and verifiers must not share a secret.- Loop detection keys on the verified
(principal, client_id, tool); a principal that can provision manyclient_ids can fan out across buckets. That is a provisioning-quota problem, stated rather than solved. - The GitHub write path (
src/mcpgov/github.py) is at-least-once made effectively-once by reconciliation — exactly-once across two systems with no shared transaction does not exist, and its list endpoint lags a successful create by ~5-6s (measured), which is exactly why its reconciler polls past the lag and refuses to create after a short-deadline miss. Its suite runs against a recorded fake with an offline guard test.
Layout
src/mcpgov/
auth.py tokens, RFC 7523 assertion exchange, group->team mapping
db.py pool, tenant-scoped connections, migration + grants
schema.sql tables, FORCE RLS policies, the audit chain head
idempotency.py the claim-then-execute ledger
limiter.py GCRA shaper + loop breaker (the two-layer argument)
audit.py HMAC hash chain: append, verify, truncation detection
server.py the five tools and the guard middleware
github.py writing to a second system that has no idempotency
cli.py migrate / seed / token / serve / verify-audit
tests/ 100 tests; Postgres-backed ones run against a real database
demos/session.py the 13-act adversarial session over real HTTP
scripts/ the seeded limiter evaluation
results/ committed evidence: eval numbers, demo transcript
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。